Understanding public perception of electric vehicles(EVs)is imperative for increasing EV adoption,which can significantly reduce greenhouse gas(GHG)emissions,thereby mitigating climate change and global warming.While ...Understanding public perception of electric vehicles(EVs)is imperative for increasing EV adoption,which can significantly reduce greenhouse gas(GHG)emissions,thereby mitigating climate change and global warming.While most existing research characterizes public perception of EV in the context of surveys,questionnaires,or interviews,our study leverages Reddit online social network(OSN)data to capture EV public perception at a much larger scale.We have collected 3,437,917 Reddit posts(including 274,979 submissions and 3,162,938 comments)between January 2011 and December 2020 relevant to EVs and analyzed them along several axes to understand how EVs are perceived by the public on Reddit through the following research questions:(1)What EVrelated topics have been discussed by Reddit users?Whether/how Reddit users’interest in different topics has changed during 2011–2020?(2)What sentiment do Reddit users hold towards EVs?Whether public sentiment on Reddit has shifted over the past 10 years?(3)Whether/how do various Reddit communities(i.e.,subreddits)have different perceptions of EVs?Our analysis evinces the potential of utilizing a large-scale OSN dataset for demonstrating a much wider spectrum of topics that the public is interested in than previous studies show,reveals fringe communities including r/conspiracy have many(controversial)discussions on EVs,especially on the environmental impacts of EVs,and one political community(r/The_Donald)has similar patterns with fringe communities in both sentiment and topic aspects.By answering these research questions,we aim to develop a more comprehensive understanding of the public perception of EVs in the past decade.展开更多
The sudden arrival of AI(Artificial Intelligence) into people's daily lives all around the world was marked by the introduction of ChatGPT, which was officially released on November 30, 2022. This AI invasion in o...The sudden arrival of AI(Artificial Intelligence) into people's daily lives all around the world was marked by the introduction of ChatGPT, which was officially released on November 30, 2022. This AI invasion in our lives drew the attention of not only tech enthusiasts but also scholars from diverse fields, as its capacity extends across various fields. Consequently, numerous articles and journals have been discussing ChatGPT, making it a headline for several topics. However, it does not reflect most public opinion about the product. Therefore, this paper investigated the public's opinions on ChatGPT through topic modelling, Vader-based sentiment analysis and SWOT analysis. To gather data for this study, 202905 comments from the Reddit platform were collected between December 2022 and December 2023. The findings reveal that the Reddit community engaged in discussions related to ChatGPT, covering a range of topics including comparisons with traditional search engines, the impacts on software development, job market, and education industry, exploring ChatGPT's responses on entertainment and politics, the responses from Dan, the alter ego of ChatGPT, the ethical usage of user data as well as queries related to the AI-generated images. The sentiment analysis indicates that most people hold positive views towards this innovative technology across these several aspects. However, concerns also arise regarding the potential negative impacts associated with this product. The SWOT analysis of these results highlights both the strengths and pain points, market opportunities and threats associated with ChatGPT. This analysis also serves as a foundation for providing recommendations aimed at the product development and policy implementation in this paper.展开更多
As blockchain technology advances,non-fungible tokens(NFTs)are emerging as unconventional assets in the commercial market.However,it is necessary to establish a comprehensive NFT ecosystem that addresses the prevailin...As blockchain technology advances,non-fungible tokens(NFTs)are emerging as unconventional assets in the commercial market.However,it is necessary to establish a comprehensive NFT ecosystem that addresses the prevailing public concerns.This study aimed to bridge this gap by analyzing user-generated content on prominent social media platforms such as Twitter,Weibo,and Reddit.Employing text clustering and topic modeling techniques,such as Latent Dirichlet Allocation,we constructed an analytical framework to delve into the intricacies of the NFT ecosystem.Our investigation revealed seven distinct topics from Twitter and Reddit data and eight topics from Weibo data.Weibo users predominantly engaged in reviews and critiques,whereas Twitter and Reddit users emphasized personal experiences and perceptions.The NFT ecosystem encompasses several crucial elements,including transactions,customers,infrastructure,products,environments,and perceptions.By identifying the prevailing trends and common issues,this study offers valuable guidance for the development of NFT ecosystems.展开更多
In 2021,the abnormal short-term price fluctuations of GameStop,which were triggered by internet stock discussions,drew the attention of academics,financial analysts,and stock trading commissions alike,prompting calls ...In 2021,the abnormal short-term price fluctuations of GameStop,which were triggered by internet stock discussions,drew the attention of academics,financial analysts,and stock trading commissions alike,prompting calls to address such events and maintain market stability.However,the impact of stock discussions on volatile trading behavior has received comparatively less attention than traditional fundamentals.Furthermore,data mining methods are less often used to predict stock trading despite their higher accuracy.This study adopts an innovative approach using social media data to obtain stock rumors,and then trains three decision trees to demonstrate the impact of rumor propagation on stock trading behavior.Our findings show that rumor propagation outperforms traditional fundamentals in predicting abnormal trading behavior.The study serves as an impetus for further research using data mining as a method of inquiry.展开更多
This study aims to identify the potential association of mental health and social media forum during the outbreak of COVID-19 pandemic.COVID-19 brings a lot of challenges to government globally.Among the different str...This study aims to identify the potential association of mental health and social media forum during the outbreak of COVID-19 pandemic.COVID-19 brings a lot of challenges to government globally.Among the different strategies the most extensively adopted ones were lockdown,social distancing,and isolation among others.Most people with no mental illness history have been found with high risk of distress and psychological discomfort due to anxiety of being infected with the virus.Panic among people due to COVID-19 spread faster than the disease itself.The misinformation and excessive usage of social media in this pandemic era have adversely affected mental health across the world.Due to limited historical data,psychiatrists are finding it difficult to cure the mental illness of people resulting from the pandemic repercussion,fueled by social media forum.In this study the methodology used for data extraction is by considering the implications of social network platforms(such as Reddit)and levering the capabilities of a semi-supervised co-training technique-based use of Naïve Bayes(NB),Random Forest(RF),and Support Vector Machine(SVM)classifiers.The experimental results shows the efficacy of the proposed methodology to identify the mental illness level(such as anxiety,bipolar disorder,depression,PTSD,schizophrenia,and OCD)of those who are in anxious of being infected with this virus.We observed 1 to 5%improvement in the classification decision through the proposed method as compared to state-of-the-art classifiers.展开更多
The massive increase in the volume of data generated by individuals on social media microblog platforms such as Twitter and Reddit every day offers researchers unique opportunities to analyze financial markets from ne...The massive increase in the volume of data generated by individuals on social media microblog platforms such as Twitter and Reddit every day offers researchers unique opportunities to analyze financial markets from new perspec-tives.The meme stock mania of 2021 brought together stock traders and investors that were also active on social media.This mania was in good part driven by retail investors’discussions on investment strategies that occurred on social media plat-forms such as Reddit during the COVID-19 lockdowns.The stock trades by these retail investors were then executed using services like Robinhood.In this paper,machine learning models are used to try and predict the stock price movements of two meme stocks:GameStop($GME)and AMC Entertainment($AMC).Two sentiment metrics of the daily social media discussions about these stocks on Red-dit are generated and used together with 85 other fundamental and technical indi-cators as the feature set for the machine learning models.It is demonstrated that through the use of a carefully chosen mix of a meme stock’s fundamental indica-tors,technical indicators,and social media sentiment scores,it is possible to pre-dict the stocks’next-day closing prices.Also,using an anomaly detection model,and the daily Reddit discussions about a meme stock,it was possible to identify potential market manipulators.展开更多
基金supported by the National Science Foundation(NSF)under Grant No.1941524 for the NSF ASPIRE ERC.
文摘Understanding public perception of electric vehicles(EVs)is imperative for increasing EV adoption,which can significantly reduce greenhouse gas(GHG)emissions,thereby mitigating climate change and global warming.While most existing research characterizes public perception of EV in the context of surveys,questionnaires,or interviews,our study leverages Reddit online social network(OSN)data to capture EV public perception at a much larger scale.We have collected 3,437,917 Reddit posts(including 274,979 submissions and 3,162,938 comments)between January 2011 and December 2020 relevant to EVs and analyzed them along several axes to understand how EVs are perceived by the public on Reddit through the following research questions:(1)What EVrelated topics have been discussed by Reddit users?Whether/how Reddit users’interest in different topics has changed during 2011–2020?(2)What sentiment do Reddit users hold towards EVs?Whether public sentiment on Reddit has shifted over the past 10 years?(3)Whether/how do various Reddit communities(i.e.,subreddits)have different perceptions of EVs?Our analysis evinces the potential of utilizing a large-scale OSN dataset for demonstrating a much wider spectrum of topics that the public is interested in than previous studies show,reveals fringe communities including r/conspiracy have many(controversial)discussions on EVs,especially on the environmental impacts of EVs,and one political community(r/The_Donald)has similar patterns with fringe communities in both sentiment and topic aspects.By answering these research questions,we aim to develop a more comprehensive understanding of the public perception of EVs in the past decade.
文摘The sudden arrival of AI(Artificial Intelligence) into people's daily lives all around the world was marked by the introduction of ChatGPT, which was officially released on November 30, 2022. This AI invasion in our lives drew the attention of not only tech enthusiasts but also scholars from diverse fields, as its capacity extends across various fields. Consequently, numerous articles and journals have been discussing ChatGPT, making it a headline for several topics. However, it does not reflect most public opinion about the product. Therefore, this paper investigated the public's opinions on ChatGPT through topic modelling, Vader-based sentiment analysis and SWOT analysis. To gather data for this study, 202905 comments from the Reddit platform were collected between December 2022 and December 2023. The findings reveal that the Reddit community engaged in discussions related to ChatGPT, covering a range of topics including comparisons with traditional search engines, the impacts on software development, job market, and education industry, exploring ChatGPT's responses on entertainment and politics, the responses from Dan, the alter ego of ChatGPT, the ethical usage of user data as well as queries related to the AI-generated images. The sentiment analysis indicates that most people hold positive views towards this innovative technology across these several aspects. However, concerns also arise regarding the potential negative impacts associated with this product. The SWOT analysis of these results highlights both the strengths and pain points, market opportunities and threats associated with ChatGPT. This analysis also serves as a foundation for providing recommendations aimed at the product development and policy implementation in this paper.
基金funded by the National Social Science Fund of China(22CTQ019).
文摘As blockchain technology advances,non-fungible tokens(NFTs)are emerging as unconventional assets in the commercial market.However,it is necessary to establish a comprehensive NFT ecosystem that addresses the prevailing public concerns.This study aimed to bridge this gap by analyzing user-generated content on prominent social media platforms such as Twitter,Weibo,and Reddit.Employing text clustering and topic modeling techniques,such as Latent Dirichlet Allocation,we constructed an analytical framework to delve into the intricacies of the NFT ecosystem.Our investigation revealed seven distinct topics from Twitter and Reddit data and eight topics from Weibo data.Weibo users predominantly engaged in reviews and critiques,whereas Twitter and Reddit users emphasized personal experiences and perceptions.The NFT ecosystem encompasses several crucial elements,including transactions,customers,infrastructure,products,environments,and perceptions.By identifying the prevailing trends and common issues,this study offers valuable guidance for the development of NFT ecosystems.
基金supported by the National Science and Technology Council,Taiwan,under grants MOST 108-2410-H-027-020,MOST 109-2410-H-027-009-MY2 and MOST 111-2410-H-027-011-MY3.
文摘In 2021,the abnormal short-term price fluctuations of GameStop,which were triggered by internet stock discussions,drew the attention of academics,financial analysts,and stock trading commissions alike,prompting calls to address such events and maintain market stability.However,the impact of stock discussions on volatile trading behavior has received comparatively less attention than traditional fundamentals.Furthermore,data mining methods are less often used to predict stock trading despite their higher accuracy.This study adopts an innovative approach using social media data to obtain stock rumors,and then trains three decision trees to demonstrate the impact of rumor propagation on stock trading behavior.Our findings show that rumor propagation outperforms traditional fundamentals in predicting abnormal trading behavior.The study serves as an impetus for further research using data mining as a method of inquiry.
文摘This study aims to identify the potential association of mental health and social media forum during the outbreak of COVID-19 pandemic.COVID-19 brings a lot of challenges to government globally.Among the different strategies the most extensively adopted ones were lockdown,social distancing,and isolation among others.Most people with no mental illness history have been found with high risk of distress and psychological discomfort due to anxiety of being infected with the virus.Panic among people due to COVID-19 spread faster than the disease itself.The misinformation and excessive usage of social media in this pandemic era have adversely affected mental health across the world.Due to limited historical data,psychiatrists are finding it difficult to cure the mental illness of people resulting from the pandemic repercussion,fueled by social media forum.In this study the methodology used for data extraction is by considering the implications of social network platforms(such as Reddit)and levering the capabilities of a semi-supervised co-training technique-based use of Naïve Bayes(NB),Random Forest(RF),and Support Vector Machine(SVM)classifiers.The experimental results shows the efficacy of the proposed methodology to identify the mental illness level(such as anxiety,bipolar disorder,depression,PTSD,schizophrenia,and OCD)of those who are in anxious of being infected with this virus.We observed 1 to 5%improvement in the classification decision through the proposed method as compared to state-of-the-art classifiers.
文摘The massive increase in the volume of data generated by individuals on social media microblog platforms such as Twitter and Reddit every day offers researchers unique opportunities to analyze financial markets from new perspec-tives.The meme stock mania of 2021 brought together stock traders and investors that were also active on social media.This mania was in good part driven by retail investors’discussions on investment strategies that occurred on social media plat-forms such as Reddit during the COVID-19 lockdowns.The stock trades by these retail investors were then executed using services like Robinhood.In this paper,machine learning models are used to try and predict the stock price movements of two meme stocks:GameStop($GME)and AMC Entertainment($AMC).Two sentiment metrics of the daily social media discussions about these stocks on Red-dit are generated and used together with 85 other fundamental and technical indi-cators as the feature set for the machine learning models.It is demonstrated that through the use of a carefully chosen mix of a meme stock’s fundamental indica-tors,technical indicators,and social media sentiment scores,it is possible to pre-dict the stocks’next-day closing prices.Also,using an anomaly detection model,and the daily Reddit discussions about a meme stock,it was possible to identify potential market manipulators.
