Spurious correlation #4,102 · View random
A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Google searches for 'that is sus' and the second variable is DexCom's stock price (DXCM). The chart goes from 2006 to 2023, and the two variables track closely in value over that time.

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Google searches for 'that is sus' and the second variable is DexCom's stock price (DXCM). The chart goes from 2006 to 2023, and the two variables track closely in value over that time.

Download png, svg

AI explanation

As the search volume for 'that is sus' rose, more people started questioning the reliability of things, including traditional glucose monitoring systems. This led to a surge in demand for DexCom's innovative continuous glucose monitoring products, causing their stock price to sweeten. It seems like investors were not willing to glucose over this opportunity to capitalize on the sus-picious trend.

^{Show image generation prompt} Model: dalle-3
Prompt: Create an image of a meme style visual where a computer screen shows a Google search bar with the words "that is sus" entered. Below the search bar, a DexCom stock price chart is displayed, and the line on the chart rises sharply. In the background, depict a bustling stock market with people looking at their devices with intrigue. The scene should have an overall mood of curiosity and potential opportunity. The depiction should include only scenes, people, and objects, it should not include text or speech bubbles.

This image generation prompt was also generated by AI, using the following sequence:

Model: gpt-3.5-turbo-1106
System prompt: You select one of a few potential scene descriptors that seems to go along with the variables described. You respond only with the scene descriptions provided and say nothing else.
User prompt: Here are two variables: Google searches for 'that is sus' and DexCom's stock price (DXCM). Given these, which of the following image style descriptions seems most appropriate? Pick the one that seems to be related to one of the variables at hand. Please respond with only one of the following potential descriptions: a funny image you would see on reddit Charcoal An image that looks like it is a scene from A Disney Movie a meme An image that looks like it is a scene from 'Star Wars'
ChatGPT: a meme

Model: gpt-3.5-turbo-1106
System prompt: You describe simple visual scenes that depict the two variables stated. You combine both variables into one scene.
User prompt: Please describe a visual scene that prominently depicts both Google searches for 'that is sus' and DexCom's stock price (DXCM), in the following situation: As the search volume for 'that is sus' rose, more people started questioning the reliability of things, including traditional glucose monitoring systems. This led to a surge in demand for DexCom's innovative continuous glucose monitoring products, causing their stock price to sweeten. It seems like investors were not willing to glucose over this opportunity to capitalize on the sus-picious trend.. Keep the description simple.
ChatGPT: In the scene, the screen of a computer or smartphone shows a Google search bar with the words "that is sus" typed in. Below it, the DexCom stock price chart is displayed, and the line on the chart rises sharply. The background of the scene depicts a bustling stock market with people looking at their devices with intrigue. The overall mood is one of curiosity and potential opportunity.

Model: gpt-3.5-turbo-1106
System prompt: You write and improve image generation prompts for DALLE-3. You maintain the same subjects, but enhance the visuals.
User prompt: Please respond with an image generation prompt that would be likely to create an interesting visual using DALLE-3, using the following style: [ a meme ] and depicting this scene: In the scene, the screen of a computer or smartphone shows a Google search bar with the words "that is sus" typed in. Below it, the DexCom stock price chart is displayed, and the line on the chart rises sharply. The background of the scene depicts a bustling stock market with people looking at their devices with intrigue. The overall mood is one of curiosity and potential opportunity. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Create an image of a meme style visual where a computer screen shows a Google search bar with the words "that is sus" entered. Below the search bar, a DexCom stock price chart is displayed, and the line on the chart rises sharply. In the background, depict a bustling stock market with people looking at their devices with intrigue. The scene should have an overall mood of curiosity and potential opportunity.

*Variations in the User Prompts from chart to chart are just the result of random number generation in Python. I wrote a few arrays of various styles and methods to ask questions to change up the results. Every time this site writes an explanation or generates an image, the script picks from each at random.

I sequence the requests into multiple prompts because I find GPT 3.5 to perform much better with short, well-managed contexts. Thus, I track the context directly in Python and only ask ChatGPT targeted questions.
^{Show prompt for explanation} Model: gpt-3.5-turbo-1106 (fine-tuned)
System prompt: You provide humorous responses in the form of plausible sounding explanations for correlations. You assume the correlation is causative for the purpose of the explanation even if it is ridiculous. You do not chat with the user, you only reply with the causal connection explanation and nothing else.
User prompt: Please make up a funny explanation for how an increase in that is sus (Google searches for 'that is sus') caused DexCom's stock price (DXCM) to increase. Include one good pun.

AI academic paper

(Because p < 0.01)

That is Suspect: Investigating the Relationship Between Google Searches for That is Sus and DexCom's Stock Price

The Journal of Digital Pop Culture Research

Jan 2024

Reminder: This paper is AI-generated. Not real!

^{Show prompt used to generate this paper} Quick note: This sequence is long and repetitive. That's how the prompt engineering works for this one. I manage the output in Python to format it into this PDF.

Model: gpt-3.5-turbo-1106
System prompt: You are a dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics journal.You draft a literature review section of an academic research paper, that starts out dry for the first few sentences but then becomes hilarious and goofy.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up a literature review section of an academic research paper presenting the findings of the connection between Google searches for 'that is sus' and DexCom's stock price (DXCM). Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

Speak in the present tense for this section (the authors find...), as is common in academic research paper literature reviews. Name the sources in a format similar to this: In "Book," the authors find lorem and ipsum.

Make up the lorem and ipsum part, but make it sound related to the topic at hand.

Start by naming serious-sounding studies by authors like Smith, Doe, and Jones - but then quickly devolve. Name some real non-fiction books that would be related to the topic. Then name some real fiction books that sound like they could be related. Then cite some social media posts you read that seem to be related.

Here is the title and abstract of the paper:
[[TITLE]]
"That is Sus"pect: Investigating the Relationship Between Google Searches for "That is Sus" and DexCom's Stock Price

[[ABSTRACT]]
This study examines the curious connection between Google searches for the phrase "That is sus" and the stock price of DexCom (DXCM). The research team utilized data from Google Trends and LSEG Analytics (Refinitiv) to conduct a thorough investigation from 2006 to 2023. Surprisingly, a strong correlation coefficient of 0.9894753 and a significance level of p < 0.01 were uncovered, indicating a striking relationship between the two seemingly unrelated phenomena. The implications of these findings are far-reaching and may have profound impacts on our understanding of market behavior and social media influence on financial markets. Furthermore, the evident resonance between the peculiar phrase and the stock price sparks intrigue and prompts a broader inquiry into the underlying mechanisms at play.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
INTRODUCTION
The intersection of social media and financial markets has become an area of increasing interest and scrutiny in recent years. With the rise of online communities and the blurring of boundaries between virtual spaces and real-world consequences, it has become imperative to explore the potential impact of digital discourse on market dynamics. In line with this burgeoning interest, our study delves into the enigmatic relationship between Google searches for the colloquial phrase "That is sus" and the stock price of DexCom (DXCM).
Certainly, the phrase "That is sus" has permeated online conversations, particularly within the realm of gaming and popular culture. Its usage to denote suspicion or distrust has garnered widespread recognition, even spilling over into everyday vernacular. While initial impressions might dismiss this phenomenon as a mere meme or passing fad, our investigation uncovers a surprisingly robust correlation between the frequency of Google searches for this phrase and the fluctuations in DexCom's stock price.
At first glance, one might be inclined to label the association between a seemingly innocuous internet search trend and corporate financial performance as purely coincidental. However, the compelling statistical evidence and rigorous analysis presented in this study challenge such dismissive interpretations. The striking correlation coefficient of 0.9894753, coupled with a significance level of p < 0.01, highlights the remarkable concordance between the two disparate domains. Indeed, the magnitude of the correlation prompts one to pause and reflect on the intricate interplay between social media expressions and market behaviors.
This unexpected connection piques curiosity and incites further inquiry into the underlying mechanisms driving these seemingly incongruent phenomena. As we venture forth into the labyrinth of digital footprints and stock market trajectories, our quest is guided by a blend of skepticism and fascination. The implications of our findings ripple through the realms of financial analysis, social media dynamics, and perhaps even cultural anthropology. Thus, with this study, we endeavor to unravel the enigma of "That is sus" and its cryptic influence on the stock price of DexCom, while also shedding light on the nuanced interdependencies in the digital age.

-------

Your response should start like this:

[[LITERATURE REVIEW]]

ChatGPT:
[[LITERATURE REVIEW]]

Numerous scholarly inquiries have delved into the perplexing realm of the interplay between social media trends and financial market dynamics. The study by Smith et al. (2018) examined the impact of Twitter sentiment on stock prices, revealing a moderate but discernible correlation in certain market conditions. Similarly, Doe and Jones (2017) explored the relationship between Facebook trends and consumer behavior, uncovering intriguing patterns in purchase decisions. These investigations underscore the significance of online discourse in shaping economic landscapes, providing a foundation for our exploration into the association between Google searches for "That is sus" and DexCom's stock price.

Turning to the realm of non-fiction literature, "The Age of Surveillance Capitalism" by Shoshana Zuboff offers valuable insights into the pervasive influence of digital platforms on individual behavior and societal trends. Furthermore, "Freakonomics" by Steven D. Levitt and Stephen J. Dubner presents a compelling case for uncovering hidden correlations and causalities in ostensibly unrelated phenomena, inspiring our pursuit of the enigmatic connection between a popular internet phrase and stock market fluctuations. In a more whimsical vein, "Alice's Adventures in Wonderland" by Lewis Carroll and "Catch-22" by Joseph Heller subtly resonate with the confounding nature of our investigation, hinting at the surreal and paradoxical dimensions of our findings.

Beyond the confines of traditional literature, social media platforms have emerged as unconventional but intriguing sources of anecdotal evidence. Anecdotal reports from platforms such as Reddit and Twitter have highlighted instances where discussions on "That is sus" appear to coincide with notable shifts in DexCom's stock price, providing anecdotal evidence that piques our interest. These unconventional sources serve as snapshots of digital discourse, fueling our curiosity and prompting a nuanced examination of the connection between online expressions and market behavior.

In synthesizing these diverse strands of inquiry and inspiration, our study ventures into uncharted territories, guided by a spirit of inquiry and a touch of whimsy, seeking to unravel the intricate web of causality and correlation linking Google searches for "That is sus" to the stock price of DexCom (DXCM).

Model: gpt-3.5-turbo-1106
System prompt: You are a dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics journal.You draft the methodology section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up the methodology section of an academic research paper presenting the findings of the connection between Google searches for 'that is sus' and DexCom's stock price (DXCM). Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

Your research team collected data from all across the internet, but mostly just used information from Google Trends and LSEG Analytics (Refinitiv) . You used data from 2006 to 2023

Make up the research methods you don't know. Make them a bit goofy and convoluted.

Here is the title, abstract, and introduction of the paper:
[[TITLE]]
"That is Sus"pect: Investigating the Relationship Between Google Searches for "That is Sus" and DexCom's Stock Price

[[ABSTRACT]]
This study examines the curious connection between Google searches for the phrase "That is sus" and the stock price of DexCom (DXCM). The research team utilized data from Google Trends and LSEG Analytics (Refinitiv) to conduct a thorough investigation from 2006 to 2023. Surprisingly, a strong correlation coefficient of 0.9894753 and a significance level of p < 0.01 were uncovered, indicating a striking relationship between the two seemingly unrelated phenomena. The implications of these findings are far-reaching and may have profound impacts on our understanding of market behavior and social media influence on financial markets. Furthermore, the evident resonance between the peculiar phrase and the stock price sparks intrigue and prompts a broader inquiry into the underlying mechanisms at play.

[[INTRODUCTION]]
INTRODUCTION
The intersection of social media and financial markets has become an area of increasing interest and scrutiny in recent years. With the rise of online communities and the blurring of boundaries between virtual spaces and real-world consequences, it has become imperative to explore the potential impact of digital discourse on market dynamics. In line with this burgeoning interest, our study delves into the enigmatic relationship between Google searches for the colloquial phrase "That is sus" and the stock price of DexCom (DXCM).
Certainly, the phrase "That is sus" has permeated online conversations, particularly within the realm of gaming and popular culture. Its usage to denote suspicion or distrust has garnered widespread recognition, even spilling over into everyday vernacular. While initial impressions might dismiss this phenomenon as a mere meme or passing fad, our investigation uncovers a surprisingly robust correlation between the frequency of Google searches for this phrase and the fluctuations in DexCom's stock price.
At first glance, one might be inclined to label the association between a seemingly innocuous internet search trend and corporate financial performance as purely coincidental. However, the compelling statistical evidence and rigorous analysis presented in this study challenge such dismissive interpretations. The striking correlation coefficient of 0.9894753, coupled with a significance level of p < 0.01, highlights the remarkable concordance between the two disparate domains. Indeed, the magnitude of the correlation prompts one to pause and reflect on the intricate interplay between social media expressions and market behaviors.
This unexpected connection piques curiosity and incites further inquiry into the underlying mechanisms driving these seemingly incongruent phenomena. As we venture forth into the labyrinth of digital footprints and stock market trajectories, our quest is guided by a blend of skepticism and fascination. The implications of our findings ripple through the realms of financial analysis, social media dynamics, and perhaps even cultural anthropology. Thus, with this study, we endeavor to unravel the enigma of "That is sus" and its cryptic influence on the stock price of DexCom, while also shedding light on the nuanced interdependencies in the digital age.

-------

Your response should start like this:

[[METHODOLOGY]]

ChatGPT:

[[METHODOLOGY]]

Data Collection:
The data for this study was sourced from Google Trends and LSEG Analytics (Refinitiv), providing a comprehensive snapshot of Google searches for the phrase "That is sus" and the stock price of DexCom (DXCM) from 2006 to 2023. A deliberate choice was made to focus on Google searches as a proxy for public interest and sentiment surrounding the colloquial expression. The decision to include data up to 2023 was motivated by the desire to capture any potential long-term trends or evolving patterns in the relationship under investigation.

Google Searches for "That is sus":
The search data for the term "That is sus" was obtained from Google Trends, a tool that aggregates and anonymizes Google search data. The frequency of searches, geospatial distribution, and related queries were analyzed to discern patterns and trends in the use of the phrase over time. Furthermore, natural language processing techniques were employed to identify semantic shifts and contextual nuances in the online discourse surrounding the term.

DexCom's Stock Price (DXCM):
LSEG Analytics (Refinitiv) facilitated access to historical stock price data for DexCom (DXCM), allowing for a meticulous examination of price movements, trading volumes, and related market indicators. In addition to the raw stock prices, various financial metrics and event-related data were considered to contextualize the stock's performance within the broader market landscape.

Statistical Analysis:
To assess the relationship between Google searches for "That is sus" and DexCom's stock price, a series of statistical analyses were performed. Firstly, an autoregressive integrated moving average (ARIMA) model was employed to account for potential time-series dependencies and seasonal fluctuations in both the search data and stock prices. Subsequently, cross-correlation functions and Granger causality tests were conducted to ascertain the direction and strength of any causal link between the search trend and stock performance.

Machine Learning Approaches:
Leveraging insights from machine learning methodologies, sentiment analysis algorithms were applied to the search data to discern underlying sentiments and emotional valence associated with instances of "That is sus" queries. These sentiment scores were then integrated into time-series models and regression analyses to explore potential mediating factors and behavioral drivers influencing the observed relationship.

Ethical Considerations:
Throughout the data collection and analysis process, stringent adherence to data privacy regulations and ethical guidelines was paramount. Steps were taken to ensure the anonymization and aggregation of individual search queries, and the utilization of stock price data in compliance with proprietary rights and usage agreements.

Limitations and Assumptions:
It is imperative to acknowledge the inherent limitations and assumptions underpinning this study. While efforts were made to account for confounding variables and external influences, the complex nature of market dynamics and online behaviors introduces an element of unpredictability. Additionally, the assumptions of stationarity in time-series data and the generalizability of sentiment analysis techniques warrant careful consideration in interpreting the results.

In summary, the methodology employed in this investigation encompassed a multi-faceted approach, integrating traditional statistical analyses with cutting-edge machine learning techniques to elucidate the intricate interplay between Google searches for "That is sus" and DexCom's stock price.

Model: gpt-3.5-turbo-1106
System prompt: You are a dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics journal.You draft the results section of an academic research paper. You speak in the past tense (you found...).
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up the results section of an academic research paper presenting the findings of the connection between Google searches for 'that is sus' and DexCom's stock price (DXCM). Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

Your research team collected data from all across the internet, but mostly just used information from Google Trends and LSEG Analytics (Refinitiv) .

For the time period 2006 to 2023, you found a correlation 0.9894753, r-squared of 0.9790614, and p < 0.01.

One figure will be included. The figure (Fig. 1) is a scatterplot showing the strong correlation between the two variables. You don't need to specify where; I will add the figure.

Here is the title and abstract of the paper:
[[TITLE]]
"That is Sus"pect: Investigating the Relationship Between Google Searches for "That is Sus" and DexCom's Stock Price

[[ABSTRACT]]
This study examines the curious connection between Google searches for the phrase "That is sus" and the stock price of DexCom (DXCM). The research team utilized data from Google Trends and LSEG Analytics (Refinitiv) to conduct a thorough investigation from 2006 to 2023. Surprisingly, a strong correlation coefficient of 0.9894753 and a significance level of p < 0.01 were uncovered, indicating a striking relationship between the two seemingly unrelated phenomena. The implications of these findings are far-reaching and may have profound impacts on our understanding of market behavior and social media influence on financial markets. Furthermore, the evident resonance between the peculiar phrase and the stock price sparks intrigue and prompts a broader inquiry into the underlying mechanisms at play.

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
INTRODUCTION
The intersection of social media and financial markets has become an area of increasing interest and scrutiny in recent years. With the rise of online communities and the blurring of boundaries between virtual spaces and real-world consequences, it has become imperative to explore the potential impact of digital discourse on market dynamics. In line with this burgeoning interest, our study delves into the enigmatic relationship between Google searches for the colloquial phrase "That is sus" and the stock price of DexCom (DXCM).
Certainly, the phrase "That is sus" has permeated online conversations, particularly within the realm of gaming and popular culture. Its usage to denote suspicion or distrust has garnered widespread recognition, even spilling over into everyday vernacular. While initial impressions might dismiss this phenomenon as a mere meme or passing fad, our investigation uncovers a surprisingly robust correlation between the frequency of Google searches for this phrase and the fluctuations in DexCom's stock price.
At first glance, one might be inclined to label the association between a seemingly innocuous internet search trend and corporate financial performance as purely coincidental. However, the compelling statistical evidence and rigorous analysis presented in this study challenge such dismissive interpretations. The striking correlation coefficient of 0.9894753, coupled with a significance level of p < 0.01, highlights the remarkable concordance between the two disparate domains. Indeed, the magnitude of the correlation prompts one to pause and reflect on the intricate interplay between social media expressions and market behaviors.
This unexpected connection piques curiosity and incites further inquiry into the underlying mechanisms driving these seemingly incongruent phenomena. As we venture forth into the labyrinth of digital footprints and stock market trajectories, our quest is guided by a blend of skepticism and fascination. The implications of our findings ripple through the realms of financial analysis, social media dynamics, and perhaps even cultural anthropology. Thus, with this study, we endeavor to unravel the enigma of "That is sus" and its cryptic influence on the stock price of DexCom, while also shedding light on the nuanced interdependencies in the digital age.

-------

Your response should start like this:

[[RESULTS]]

ChatGPT:

[[RESULTS]]

The statistical analysis revealed a remarkably strong correlation between Google searches for "That is sus" and the stock price of DexCom (DXCM) over the period from 2006 to 2023. The correlation coefficient of 0.9894753 indicates an almost perfect positive linear relationship between the two variables. This finding suggests that as the frequency of Google searches for "That is sus" fluctuated, so did the stock price of DexCom, reinforcing the notion that even the most unexpected and seemingly frivolous online expressions may have tangible effects on financial markets.

Furthermore, the R-squared value of 0.9790614 signifies that approximately 97.9% of the variability in DexCom's stock price can be explained by fluctuations in Google searches for "That is sus." While causation cannot be inferred from these results, the strength of this explanatory power is striking and evokes questions about the mechanisms underlying this peculiar relationship. It appears that the phrase "That is sus," which originated in online gaming communities, has transcended its humble origins to potentially exert a palpable influence on the valuations of a biomedical technology company.

The p-value of less than 0.01 reinforces the robustness of the observed relationship, indicating that the likelihood of such a strong association occurring by random chance is exceedingly low. This statistical significance underscores the substantive nature of the connection between social media expressions and stock market dynamics, prompting a reevaluation of the ways in which digital discourse intersects with financial phenomena.

As shown in Fig. 1, the scatterplot visually depicts the tightly clustered data points, affirming the strength of the correlation between Google searches for "That is sus" and DexCom's stock price. The plot is a testament to the unexpected nature of our findings and the need for a comprehensive examination of the interplay between online trends and market fluctuations.

In summary, the results of this investigation illuminate a compelling correspondence between the frequency of Google searches for "That is sus" and the movements of DexCom's stock price, challenging traditional notions of market influences and emphasizing the noteworthy impact of digital expressions on financial dynamics. These findings engender a newfound appreciation for the intricate and often whimsical undercurrents that shape the behavior of markets, and they emphasize the imperative of embracing unconventional sources of insight in understanding contemporary economic phenomena.

Model: gpt-3.5-turbo-1106
System prompt: You are a dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics journal.You draft the discussion section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up the discussion section of an academic research paper presenting the findings of the connection between Google searches for 'that is sus' and DexCom's stock price (DXCM). Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

Limit your response to 500 tokens.

Here are the title, abstract, literature review, and results sections. Please harken back to 1-2 of the goofy items in the literature review, but pretend to take them completely seriously. Discuss how your results supported the prior research.

Do not write a conclusion. I will add a conclusion after this.

[[TITLE]]
"That is Sus"pect: Investigating the Relationship Between Google Searches for "That is Sus" and DexCom's Stock Price

[[ABSTRACT]]
This study examines the curious connection between Google searches for the phrase "That is sus" and the stock price of DexCom (DXCM). The research team utilized data from Google Trends and LSEG Analytics (Refinitiv) to conduct a thorough investigation from 2006 to 2023. Surprisingly, a strong correlation coefficient of 0.9894753 and a significance level of p < 0.01 were uncovered, indicating a striking relationship between the two seemingly unrelated phenomena. The implications of these findings are far-reaching and may have profound impacts on our understanding of market behavior and social media influence on financial markets. Furthermore, the evident resonance between the peculiar phrase and the stock price sparks intrigue and prompts a broader inquiry into the underlying mechanisms at play.

[[LITERATURE REVIEW]]
Numerous scholarly inquiries have delved into the perplexing realm of the interplay between social media trends and financial market dynamics. The study by Smith et al. (2018) examined the impact of Twitter sentiment on stock prices, revealing a moderate but discernible correlation in certain market conditions. Similarly, Doe and Jones (2017) explored the relationship between Facebook trends and consumer behavior, uncovering intriguing patterns in purchase decisions. These investigations underscore the significance of online discourse in shaping economic landscapes, providing a foundation for our exploration into the association between Google searches for "That is sus" and DexCom's stock price.
Turning to the realm of non-fiction literature, "The Age of Surveillance Capitalism" by Shoshana Zuboff offers valuable insights into the pervasive influence of digital platforms on individual behavior and societal trends. Furthermore, "Freakonomics" by Steven D. Levitt and Stephen J. Dubner presents a compelling case for uncovering hidden correlations and causalities in ostensibly unrelated phenomena, inspiring our pursuit of the enigmatic connection between a popular internet phrase and stock market fluctuations. In a more whimsical vein, "Alice's Adventures in Wonderland" by Lewis Carroll and "Catch-22" by Joseph Heller subtly resonate with the confounding nature of our investigation, hinting at the surreal and paradoxical dimensions of our findings.
Beyond the confines of traditional literature, social media platforms have emerged as unconventional but intriguing sources of anecdotal evidence. Anecdotal reports from platforms such as Reddit and Twitter have highlighted instances where discussions on "That is sus" appear to coincide with notable shifts in DexCom's stock price, providing anecdotal evidence that piques our interest. These unconventional sources serve as snapshots of digital discourse, fueling our curiosity and prompting a nuanced examination of the connection between online expressions and market behavior.
In synthesizing these diverse strands of inquiry and inspiration, our study ventures into uncharted territories, guided by a spirit of inquiry and a touch of whimsy, seeking to unravel the intricate web of causality and correlation linking Google searches for "That is sus" to the stock price of DexCom (DXCM).

[[RESULTS]]
The statistical analysis revealed a remarkably strong correlation between Google searches for "That is sus" and the stock price of DexCom (DXCM) over the period from 2006 to 2023. The correlation coefficient of 0.9894753 indicates an almost perfect positive linear relationship between the two variables. This finding suggests that as the frequency of Google searches for "That is sus" fluctuated, so did the stock price of DexCom, reinforcing the notion that even the most unexpected and seemingly frivolous online expressions may have tangible effects on financial markets.
Furthermore, the R-squared value of 0.9790614 signifies that approximately 97.9% of the variability in DexCom's stock price can be explained by fluctuations in Google searches for "That is sus." While causation cannot be inferred from these results, the strength of this explanatory power is striking and evokes questions about the mechanisms underlying this peculiar relationship. It appears that the phrase "That is sus," which originated in online gaming communities, has transcended its humble origins to potentially exert a palpable influence on the valuations of a biomedical technology company.
The p-value of less than 0.01 reinforces the robustness of the observed relationship, indicating that the likelihood of such a strong association occurring by random chance is exceedingly low. This statistical significance underscores the substantive nature of the connection between social media expressions and stock market dynamics, prompting a reevaluation of the ways in which digital discourse intersects with financial phenomena.
As shown in Fig. 1, the scatterplot visually depicts the tightly clustered data points, affirming the strength of the correlation between Google searches for "That is sus" and DexCom's stock price. The plot is a testament to the unexpected nature of our findings and the need for a comprehensive examination of the interplay between online trends and market fluctuations.
In summary, the results of this investigation illuminate a compelling correspondence between the frequency of Google searches for "That is sus" and the movements of DexCom's stock price, challenging traditional notions of market influences and emphasizing the noteworthy impact of digital expressions on financial dynamics. These findings engender a newfound appreciation for the intricate and often whimsical undercurrents that shape the behavior of markets, and they emphasize the imperative of embracing unconventional sources of insight in understanding contemporary economic phenomena.

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

[[DISCUSSION]]

The findings of this study have implications that are as surprising as finding a hidden treasure chest in the midst of a languid meadow. Our results, which revealed a robust correlation between the frequency of Google searches for "That is sus" and the stock price of DexCom (DXCM), are in line with the prior research discussed. It seems that the amalgamation of seemingly unrelated elements, much like the concoction of a peculiar potion, can yield unexpected and meaningful outcomes.

The correlation coefficient of 0.9894753 uncovered in our study echoes the whispers of previous inquiries that hinted at the latent influence of social media expressions on financial market dynamics. This correlation coefficient is quite impressive, akin to finding a four-leaf clover in a vast field of uniform greenery. Furthermore, the R-squared value of 0.9790614 indicates that a substantial proportion of the variability in DexCom's stock price can be elucidated by fluctuations in Google searches for "That is sus." This echoes the sentiment of Smith et al. (2018) and Doe and Jones (2017), who uncovered discernible relationships between social media trends and economic variables, albeit in different contexts.

The statistical significance of the observed relationship, as indicated by the p-value of less than 0.01, reinforces the weight of our findings. This adds a touch of gravitas to the otherwise whimsical connection between an internet catchphrase and a biomedical technology company's stock price. The conclusion seems nothing short of a delightful surprise, much like stumbling upon a blooming garden in the middle of a desert.

The scatterplot presented in our results further underscores the strength of the correlation, serving as a visual testament to the unexpected nature of our findings. It brings to mind the art of connect-the-dots, where seemingly disparate points form a coherent picture when joined together, much like the amalgamation of "That is sus" and DexCom's stock price.

In essence, this study provides empirical validation for the whimsical notion that even the quirkiest of online expressions may exert tangible influence on the behavior of financial markets. Much like the hidden comedic anecdotes in the works of Lewis Carroll and Joseph Heller, our findings challenge conventional wisdom and highlight the need for a more nuanced understanding of the interplay between digital discourse and market fluctuations. This paves the way for future research to delve further into the enthralling realm of social media influence on financial markets and prompts a reevaluation of the quaint and often overlooked connections that shape our economic landscapes.

Model: gpt-3.5-turbo-1106
System prompt: You are a dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics journal.You draft the discussion section of goofy academic research papers that sounds like it belongs based on the title and abstract provided.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up a short conclusion of an academic research paper presenting the findings of the connection between Google searches for 'that is sus' and DexCom's stock price (DXCM). Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

Limit your response to 300 tokens. At the very end, assert that no more research is needed in this area.

Here are the title, abstract, introduction, and results sections.
[[TITLE]]
"That is Sus"pect: Investigating the Relationship Between Google Searches for "That is Sus" and DexCom's Stock Price

[[ABSTRACT]]
This study examines the curious connection between Google searches for the phrase "That is sus" and the stock price of DexCom (DXCM). The research team utilized data from Google Trends and LSEG Analytics (Refinitiv) to conduct a thorough investigation from 2006 to 2023. Surprisingly, a strong correlation coefficient of 0.9894753 and a significance level of p < 0.01 were uncovered, indicating a striking relationship between the two seemingly unrelated phenomena. The implications of these findings are far-reaching and may have profound impacts on our understanding of market behavior and social media influence on financial markets. Furthermore, the evident resonance between the peculiar phrase and the stock price sparks intrigue and prompts a broader inquiry into the underlying mechanisms at play.

[[INTRDUCTION]]
INTRODUCTION
The intersection of social media and financial markets has become an area of increasing interest and scrutiny in recent years. With the rise of online communities and the blurring of boundaries between virtual spaces and real-world consequences, it has become imperative to explore the potential impact of digital discourse on market dynamics. In line with this burgeoning interest, our study delves into the enigmatic relationship between Google searches for the colloquial phrase "That is sus" and the stock price of DexCom (DXCM).
Certainly, the phrase "That is sus" has permeated online conversations, particularly within the realm of gaming and popular culture. Its usage to denote suspicion or distrust has garnered widespread recognition, even spilling over into everyday vernacular. While initial impressions might dismiss this phenomenon as a mere meme or passing fad, our investigation uncovers a surprisingly robust correlation between the frequency of Google searches for this phrase and the fluctuations in DexCom's stock price.
At first glance, one might be inclined to label the association between a seemingly innocuous internet search trend and corporate financial performance as purely coincidental. However, the compelling statistical evidence and rigorous analysis presented in this study challenge such dismissive interpretations. The striking correlation coefficient of 0.9894753, coupled with a significance level of p < 0.01, highlights the remarkable concordance between the two disparate domains. Indeed, the magnitude of the correlation prompts one to pause and reflect on the intricate interplay between social media expressions and market behaviors.
This unexpected connection piques curiosity and incites further inquiry into the underlying mechanisms driving these seemingly incongruent phenomena. As we venture forth into the labyrinth of digital footprints and stock market trajectories, our quest is guided by a blend of skepticism and fascination. The implications of our findings ripple through the realms of financial analysis, social media dynamics, and perhaps even cultural anthropology. Thus, with this study, we endeavor to unravel the enigma of "That is sus" and its cryptic influence on the stock price of DexCom, while also shedding light on the nuanced interdependencies in the digital age.

[[RESULTS]]
The statistical analysis revealed a remarkably strong correlation between Google searches for "That is sus" and the stock price of DexCom (DXCM) over the period from 2006 to 2023. The correlation coefficient of 0.9894753 indicates an almost perfect positive linear relationship between the two variables. This finding suggests that as the frequency of Google searches for "That is sus" fluctuated, so did the stock price of DexCom, reinforcing the notion that even the most unexpected and seemingly frivolous online expressions may have tangible effects on financial markets.
Furthermore, the R-squared value of 0.9790614 signifies that approximately 97.9% of the variability in DexCom's stock price can be explained by fluctuations in Google searches for "That is sus." While causation cannot be inferred from these results, the strength of this explanatory power is striking and evokes questions about the mechanisms underlying this peculiar relationship. It appears that the phrase "That is sus," which originated in online gaming communities, has transcended its humble origins to potentially exert a palpable influence on the valuations of a biomedical technology company.
The p-value of less than 0.01 reinforces the robustness of the observed relationship, indicating that the likelihood of such a strong association occurring by random chance is exceedingly low. This statistical significance underscores the substantive nature of the connection between social media expressions and stock market dynamics, prompting a reevaluation of the ways in which digital discourse intersects with financial phenomena.
As shown in Fig. 1, the scatterplot visually depicts the tightly clustered data points, affirming the strength of the correlation between Google searches for "That is sus" and DexCom's stock price. The plot is a testament to the unexpected nature of our findings and the need for a comprehensive examination of the interplay between online trends and market fluctuations.
In summary, the results of this investigation illuminate a compelling correspondence between the frequency of Google searches for "That is sus" and the movements of DexCom's stock price, challenging traditional notions of market influences and emphasizing the noteworthy impact of digital expressions on financial dynamics. These findings engender a newfound appreciation for the intricate and often whimsical undercurrents that shape the behavior of markets, and they emphasize the imperative of embracing unconventional sources of insight in understanding contemporary economic phenomena.

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Your response should start like this:

[[CONCLUSION]]

ChatGPT:

[[CONCLUSION]]

In conclusion, the findings of this study offer a captivating glimpse into the uncharted territory of the interrelationship between online colloquialisms and financial market dynamics. The remarkable correlation uncovered between Google searches for "That is sus" and DexCom's stock price challenges conventional wisdom, presenting a real conundrum: can the virtual realm of memes and gaming vernacular truly influence the cold, calculated world of stock prices and market valuations? It seems that the digital echoes of suspicion and distrust, encapsulated in the innocuous phrase "That is sus," reverberate through the intricacies of market behavior, leaving even the shrewdest analysts perplexed.

The 97.9% of the variability in DexCom's stock price explained by fluctuations in Google searches for "That is sus" is as shocking as finding a cryptocurrency miner in a game of Minecraft – unexpected, yet undeniably intriguing. The scatterplot, resembling a constellation of digital oddities, serves as a visual testament to this improbable union between an internet catchphrase and a biomedical technology company's stock performance. It seems that the whims and caprices of internet culture have transcended their virtual boundaries to prod at the delicate balance of market forces, not unlike a playful kitten pawing at a jigsaw puzzle.

One cannot help but ponder the broader implications of this revelation. Perhaps the idiosyncrasies of social media expressions hold greater sway than previously envisaged, acting as covert marionette strings in the intricate dance of financial markets. Just as the moon's gravitational pull influences the tides, so too may the digital zeitgeist subtly shape the undulations of stock prices.

In light of these results, it is evident that the realm of social media and its enigmatic influence on financial markets warrants further meticulous exploration. Yet, it is with a wry smile and a raised eyebrow that we assert: No more research is needed in this area.

Model: gpt-3.5-turbo-1106
System prompt: You provide fictional names of academic journals. You say nothing else, and you do not chat with the user.
User prompt: Please provide the name of a funny but plausible sounding research, scientific, or academic journal that would publish a paper entited That is Suspect: Investigating the Relationship Between Google Searches for That is Sus and DexCom's Stock Price. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Digital Pop Culture Research

Model: gpt-3.5-turbo-1106
System prompt: You provide fictional names of nonprofit research organizations and associations. You say nothing else, and you do not chat with the user.
User prompt: Please provide the name of a funny but plausible sounding nonprofit, academic, or scientific association or organization that would sponsor research that resulted in a paper entited That is Suspect: Investigating the Relationship Between Google Searches for That is Sus and DexCom's Stock Price. Respond only with the name of a fictional organization.

ChatGPT:

The Institute for Sociolinguistic Studies and Market Analysis

Model: gpt-3.5-turbo-1106
System prompt: You provide potential search keywords separated by commas. You say nothing else, and you do not chat with the user.
User prompt: Please provide potential search keywords for a paper titled That is Suspect: Investigating the Relationship Between Google Searches for That is Sus and DexCom's Stock Price with an abstract of This study examines the curious connection between Google searches for the phrase "That is sus" and the stock price of DexCom (DXCM). The research team utilized data from Google Trends and LSEG Analytics (Refinitiv) to conduct a thorough investigation from 2006 to 2023. Surprisingly, a strong correlation coefficient of 0.9894753 and a significance level of p < 0.01 were uncovered, indicating a striking relationship between the two seemingly unrelated phenomena. The implications of these findings are far-reaching and may have profound impacts on our understanding of market behavior and social media influence on financial markets. Furthermore, the evident resonance between the peculiar phrase and the stock price sparks intrigue and prompts a broader inquiry into the underlying mechanisms at play.

ChatGPT:

Google searches, "That is sus", DexCom stock price, correlation, Google Trends, LSEG Analytics, social media influence, market behavior, financial markets, stock price correlation, social media impact, market trends

*There is a bunch of Python happening behind the scenes to turn this prompt sequence into a PDF.

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Data details

Google searches for 'that is sus'
Detailed data title: Relative volume of Google searches for 'that is sus' (Worldwide, without quotes)
Source: Google Trends
Additional Info: ^{See full details} Relative search volume (not absolute numbers)

See what else correlates with Google searches for 'that is sus'

DexCom's stock price (DXCM)
Detailed data title: Opening price of DexCom (DXCM) on the first trading day of the year
Source: LSEG Analytics (Refinitiv)
Additional Info: ^{See full details} Via Microsoft Excel Stockhistory function

See what else correlates with DexCom's stock price (DXCM)

Correlation r = 0.9894753 (Pearson correlation coefficient)
Correlation is a measure of how much the variables move together. If it is 0.99, when one goes up the other goes up. If it is 0.02, the connection is very weak or non-existent. If it is -0.99, then when one goes up the other goes down. If it is 1.00, you probably messed up your correlation function.

r² = 0.9790614 (Coefficient of determination)
This means 97.9% of the change in the one variable (i.e., DexCom's stock price (DXCM)) is predictable based on the change in the other (i.e., Google searches for 'that is sus') over the 18 years from 2006 through 2023.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 7.3E-15.^Show 0.0000000000000073243224688408
The p-value is a measure of how probable it is that we would randomly find a result this extreme.^Note More specifically the p-value is a measure of how probable it is that we would randomly find a result this extreme if we had only tested one pair of variables one time.

But I am a p-villain. I absolutely did not test only one pair of variables one time. I correlated hundreds of millions of pairs of variables. I threw boatloads of data into an industrial-sized blender to find this correlation.

Who is going to stop me? p-value reporting doesn't require me to report how many calculations I had to go through in order to find a low p-value!
On average, you will find a correaltion as strong as 0.99 in 7.3E-13% of random cases. Said differently, if you correlated 136,531,399,901,385 random variables^Note You don't actually need 136 trillion variables to find a correlation like this one. I don't have that many variables in my database. You can also correlate variables that are not independent. I do this a lot.

p-value calculations are useful for understanding the probability of a result happening by chance. They are most useful when used to highlight the risk of a fluke outcome. For example, if you calculate a p-value of 0.30, the risk that the result is a fluke is high. It is good to know that! But there are lots of ways to get a p-value of less than 0.01, as evidenced by this project.

In this particular case, the values are so extreme as to be meaningless. That's why no one reports p-values with specificity after they drop below 0.01.

Just to be clear: I'm being completely transparent about the calculations. There is no math trickery. This is just how statistics shakes out when you calculate hundreds of millions of random correlations.
with the same 17 degrees of freedom, ^Note Degrees of freedom is a measure of how many free components we are testing. In this case it is 17 because we have two variables measured over a period of 18 years. It's just the number of years minus ( the number of variables minus one ), which in this case simplifies to the number of years minus one.
you would randomly expect to find a correlation as strong as this one.

[ 0.97, 1 ] 95% correlation confidence interval (using the Fisher z-transformation)
^{Read more about the confidence interval} The confidence interval is an estimate the range of the value of the correlation coefficient, using the correlation itself as an input. The values are meant to be the low and high end of the correlation coefficient with 95% confidence.

This one is a bit more complciated than the other calculations, but I include it because many people have been pushing for confidence intervals instead of p-value calculations (for example: NEJM. However, if you are dredging data, you can reliably find yourself in the 5%. That's my goal!

All values for the years included above: ^Note If I were being very sneaky, I could trim years from the beginning or end of the datasets to increase the correlation on some pairs of variables. I don't do that because there are already plenty of correlations in my database without monkeying with the years.

Still, sometimes one of the variables has more years of data available than the other. This page only shows the overlapping years. To see all the years, click on "See what else correlates with..." link above.

	2006	2007	2008	2009	2010	2011	2012	2013	2014	2015	2016	2017	2018	2019	2020	2021	2022	2023
Google searches for 'that is sus' (Rel. search volume)	8.66667	3.83333	1.33333	6.41667	5.58333	6.91667	10.25	10.0833	8.66667	8.66667	11.0833	12.5	15.4167	14.4167	40.8333	58.1667	81.6667	79.6
DexCom's stock price (DXCM) (Stock price)	3.75	2.49	2.26	0.69	2.05	3.44	2.38	3.47	8.81	13.91	20.07	14.88	14.41	29.25	54.64	91.52	132.95	114.3

Why this works

Data dredging: I have 25,153 variables in my database. I compare all these variables against each other to find ones that randomly match up. That's 632,673,409 correlation calculations! This is called “data dredging.” Instead of starting with a hypothesis and testing it, I instead abused the data to see what correlations shake out. It’s a dangerous way to go about analysis, because any sufficiently large dataset will yield strong correlations completely at random.
Lack of causal connection: There is probably^Note Because these pages are automatically generated, it's possible that the two variables you are viewing are in fact causually related. I take steps to prevent the obvious ones from showing on the site (I don't let data about the weather in one city correlate with the weather in a neighboring city, for example), but sometimes they still pop up. If they are related, cool! You found a loophole.
no direct connection between these variables, despite what the AI says above. This is exacerbated by the fact that I used "Years" as the base variable. Lots of things happen in a year that are not related to each other! Most studies would use something like "one person" in stead of "one year" to be the "thing" studied.
Observations not independent: For many variables, sequential years are not independent of each other. If a population of people is continuously doing something every day, there is no reason to think they would suddenly change how they are doing that thing on January 1. A simple^Note Personally I don't find any p-value calculation to be 'simple,' but you know what I mean.
p-value calculation does not take this into account, so mathematically it appears less probable than it really is.

Try it yourself

You can calculate the values on this page on your own! Try running the Python code to see the calculation results. ^{Show the steps to do this.} Step 1: Download and install Python on your computer.

Step 2: Open a plaintext editor like Notepad and paste the code below into it.

Step 3: Save the file as "calculate_correlation.py" in a place you will remember, like your desktop. Copy the file location to your clipboard. On Windows, you can right-click the file and click "Properties," and then copy what comes after "Location:" As an example, on my computer the location is "C:\Users\tyler\Desktop"

Step 4: Open a command line window. For example, by pressing start and typing "cmd" and them pressing enter.

Step 5: Install the required modules by typing "pip install numpy", then pressing enter, then typing "pip install scipy", then pressing enter.

Step 6: Navigate to the location where you saved the Python file by using the "cd" command. For example, I would type "cd C:\Users\tyler\Desktop" and push enter.

Step 7: Run the Python script by typing "python calculate_correlation.py"

If you run into any issues, I suggest asking ChatGPT to walk you through installing Python and running the code below on your system. Try this question:

"Walk me through installing Python on my computer to run a script that uses scipy and numpy. Go step-by-step and ask me to confirm before moving on. Start by asking me questions about my operating system so that you know how to proceed. Assume I want the simplest installation with the latest version of Python and that I do not currently have any of the necessary elements installed. Remember to only give me one step per response and confirm I have done it before proceeding."

# These modules make it easier to perform the calculation
import numpy as np
from scipy import stats

# We'll define a function that we can call to return the correlation calculations
def calculate_correlation(array1, array2):

    # Calculate Pearson correlation coefficient and p-value
    correlation, p_value = stats.pearsonr(array1, array2)

    # Calculate R-squared as the square of the correlation coefficient
    r_squared = correlation**2

    return correlation, r_squared, p_value

# These are the arrays for the variables shown on this page, but you can modify them to be any two sets of numbers
array_1 = np.array([8.66667,3.83333,1.33333,6.41667,5.58333,6.91667,10.25,10.0833,8.66667,8.66667,11.0833,12.5,15.4167,14.4167,40.8333,58.1667,81.6667,79.6,])
array_2 = np.array([3.75,2.49,2.26,0.69,2.05,3.44,2.38,3.47,8.81,13.91,20.07,14.88,14.41,29.25,54.64,91.52,132.95,114.3,])
array_1_name = "Google searches for 'that is sus'"
array_2_name = "DexCom's stock price (DXCM)"

# Perform the calculation
print(f"Calculating the correlation between {array_1_name} and {array_2_name}...")
correlation, r_squared, p_value = calculate_correlation(array_1, array_2)

# Print the results
print("Correlation Coefficient:", correlation)
print("R-squared:", r_squared)
print("P-value:", p_value)

Reuseable content

You may re-use the images on this page for any purpose, even commercial purposes, without asking for permission. The only requirement is that you attribute Tyler Vigen. ^Note Attribution can take many different forms. If you leave the "tylervigen.com" link in the image, that satisfies it just fine. If you remove it and move it to a footnote, that's fine too. You can also just write "Charts courtesy of Tyler Vigen" at the bottom of an article.

You do not need to attribute "the spurious correlations website," and you don't even need to link here if you don't want to. I don't gain anything from pageviews. There are no ads on this site, there is nothing for sale, and I am not for hire.

For the record, I am just one person. Tyler Vigen, he/him/his. I do have degrees, but they should not go after my name unless you want to annoy my wife. If that is your goal, then go ahead and cite me as "Tyler Vigen, A.A. A.A.S. B.A. J.D." Otherwise it is just "Tyler Vigen."

When spoken, my last name is pronounced "vegan," like I don't eat meat.

Full license details.
For more on re-use permissions, or to get a signed release form, see tylervigen.com/permission.

Download images for these variables:

High resolution line chart ^Note The image linked here is a Scalable Vector Graphic (SVG). It is the highest resolution that is possible to achieve. It scales up beyond the size of the observable universe without pixelating. You do not need to email me asking if I have a higher resolution image. I do not. The physical limitations of our universe prevent me from providing you with an image that is any higher resolution than this one.

If you insert it into a PowerPoint presentation (a tool well-known for managing things that are the scale of the universe), you can right-click > "Ungroup" or "Create Shape" and then edit the lines and text directly. You can also change the colors this way.

Alternatively you can use a tool like Inkscape.
High resolution line chart, optimized for mobile
Alternative high resolution line chart
Scatterplot
Portable line chart (png)
Portable line chart (png), optimized for mobile
Line chart for only Google searches for 'that is sus'
Line chart for only DexCom's stock price (DXCM)
AI-generated correlation image
The spurious research paper: That is Suspect: Investigating the Relationship Between Google Searches for That is Sus and DexCom's Stock Price

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Correlation ID: 4102 · Black Variable ID: 1367 · Red Variable ID: 1782


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