How are social and mass media different in relation to the stock market? A study on topic coverage and predictive value

Dong, Hang; Ren, Assistant Professor of Information Systems Jie; Padmanabhan, Professor Balaji; Nickerson, Professor Jeffrey V.

doi:10.1016/j.im.2021.103588

Cited by 17 publications

(8 citation statements)

References 76 publications

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“…Mass media, such as newspapers, television, radio, and online news outlets, have played an important role in disseminating information for investment decisions over the years (Dong et al 2022). Before social media became influential, mass media was used to provide information to all investor types.…”

Section: Discussionmentioning

confidence: 99%

“…Before social media became influential, mass media was used to provide information to all investor types. The information content of mass media is much larger than that of social media (Dong et al 2022). Mass media was popular among investors because it disseminated information, created sentiment, provided advice and forecasting, covered sensational news, and provided education and awareness services, among many other reasons.…”

Section: Discussionmentioning

confidence: 99%

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Information Sources for Investment Decisions: Evidence from Japanese Investors

Lal,

Sulemana,

Nguyen

et al. 2023

IJFS

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Although the traditional sources of financial knowledge in Japan are financial advisors and investment groups, the digital era and artificial intelligence have made other sources of information, such as social media and mass media, more influential. As such, it has become important to examine the socioeconomic, demographic, and psychological factors influencing the use of these information sources in the context of investment decisions. However, little research has been carried out to examine such associations using a large-scale nationwide dataset. We fill this gap by utilizing a dataset comprising almost 65,000 active investors from one of the largest online security companies in Japan, ensuring the representativeness and generalizability of our results. We show that active investors are more inclined to use social media and mass media than financial advisors and investment groups. The probit regression model shows that the use of each of the four sources of information is strongly shaped by an individual’s characteristics, which, to some extent, are not mutually exclusive for each source type. The study results imply that the government should regulate and monitor the quality and accuracy of the information disseminated by mass media and social media and educate investors on how to critically evaluate and verify the information that they receive.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Information Sources for Investment Decisions: Evidence from Japanese Investors

Lal,

Sulemana,

Nguyen

et al. 2023

IJFS

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show abstract

“…There are several methods to measure investor attention in the existing literature. Some researchers use the media coverage intensity as a measure of investor attention (Dong et al, 2022), and others use data on investor–firm interactions, such as postings or comments on firms' official social media accounts, forums, and online communities (Cade, 2018). Investor trading behaviors, such as stock trading volume or turnover rate, have also been utilized to portray investor attention (Jones et al, 1994).…”

Section: Methodsmentioning

confidence: 99%

How does investor attention affect energy firms' managerial opportunistic behavior? New evidence from China

et al. 2023

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The energy sector plays a crucial role in facilitating the low‐carbon energy transition. However, in the absence of appropriate environmental regulation, managerial opportunistic behavior in energy firms can manipulate ethical investor perceptions and hinder the real transition process towards clean energy. Using Chinese listed energy firms as the research setting, this paper examines the impact of investor attention on energy firms' earnings management practices. In both clean and traditional energy firms, the results show a significant U‐shaped association between investor attention and earnings management, with the U‐shaped curve for clean energy firms being smoother. This U‐shaped relationship is more pronounced in energy firms with larger size and weaker external monitoring. Moreover, the mediating analysis shows that internal control quality transmits the impact of investor attention onto earnings management practices in the energy sector. Our key findings remain robust to a battery of robustness tests and endogeneity controls. Therefore, given the growing attention on the energy sector, this study extends the existing literature on energy firms' managerial opportunistic behavior by analyzing the nonlinear effect for investor attention and provides practical implications for curbing energy firms' managerial opportunistic activities and guiding managerial attention towards making real sustainable investments, thereby promoting clean energy transition and sustainable development.

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“…(2015) proposed a method to extract social sentiment from influential Twitter users in the financial community, and demonstrated that the social sentiment of influential users provides stronger financial market prediction performance than ordinary social sentiment. Dong et al . (2022) compared social media and mass media in the stock market to predict future stock absolute returns, and found that mass media information coverage is more predictive than social media information coverage on a one-day horizon, whereas it is the other way around in a two-to five-day horizon.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Dong et al (2022) compared social media and mass media in the stock market to predict future stock absolute returns, and found that mass media information coverage is more predictive than social media information coverage on a one-day horizon, whereas it is the other way around in a two-to five-day horizon. The most cited work concerning the impact of social media on stock isBollen et al's (2011) study, which combines OpinionFinder and Google-Profile of Mood States to measure the public mood and reveals public mood is related to stock movements over time.…”

mentioning

confidence: 99%

How to identify influential content: Predicting retweets in online financial community

Zhong

Zhao

et al. 2023

AJIM

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PurposeRetail investors are prone to be affected by information dissemination in social media with the rapid development of Web 2.0. The purpose of this study is to recognize the factors that may impact users' retweet behavior, namely information dissemination in the online financial community, through machine learning techniques.Design/methodology/approachThis paper crawled data from the Chinese online financial community (Xueqiu.com) and extracted author-related, content-related, situation-related, stock-related and stock market-related features from the dataset. The best information dissemination prediction model based on these features was determined by evaluating five classifiers with various performance metrics, and the predictability of different feature groups was tested.FindingsFive prevalent classifiers were evaluated with various performance metrics and the random forest classifier was proven to be the best retweet prediction model in the authors’ experiments. Moreover, the predictability of author-related, content-related and market-related features was illustrated to be relatively better than that of the other two feature groups. Several particularly important features, such as the author's followers and the rise and fall of the stock index, were recognized in this paper at last.Originality/valueThis study contributes to in-depth research on information dissemination in the financial domain. The findings of this study have important practical implications for government regulators to supervise public opinion in the financial market.

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How are social and mass media different in relation to the stock market? A study on topic coverage and predictive value

Cited by 17 publications

References 76 publications

Information Sources for Investment Decisions: Evidence from Japanese Investors

Information Sources for Investment Decisions: Evidence from Japanese Investors

How does investor attention affect energy firms' managerial opportunistic behavior? New evidence from China

How to identify influential content: Predicting retweets in online financial community

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