The authors attempt to assess the opinions of investors who frequently write articles and provide comments on the social media platform Seeking Alpha (SA) and evaluate these investors’ ability to provide genuine investment advice. Their findings indicate that these investors add value and provide useful investment advice in terms of predicting future stock returns and earnings surprises.

Social media has become an integral part of the general public’s—and the investor community’s—mode of communication. Increasingly, investors are using social media to either solicit or disseminate information. As such, it is helpful for investment practitioners to have an idea of the usefulness of the investors’ opinions that circulate in social media, especially on those sites that are the most frequented by the investor community.

Given the widespread use of SA in the investor community, the authors track articles and commentaries on the site to determine the predictive power of investors’ opinions, as inferred from their articles and commentaries. Their findings indicate that use of negative words in SA articles and commentaries leads to negative stock returns over the following three months. The general interpretation of this result is that SA articles and commentaries contain valuable information that is not factored into stock prices prior to their publication. After the publication of the articles and commentaries, stock prices react to this valuable information.

Some might argue that the articles and commentaries may contain false information and investors may react to this false information, leading to movements in stock prices. The authors debunk this argument by testing the ability of SA articles and commentaries to predict earnings surprises, which shows that these articles and commentaries contain valuable information. Moreover, the authors’ findings also indicate that articles on SA have more value than those published in other, traditional media outlets—namely, Dow Jones News Service (DJNS) articles.

The authors use data collected from SA articles, SA commentaries, and DJNS articles and conduct textual analysis to quantify and study views disseminated in these articles. Similarly, they use financial analyst data from Institutional Brokers’ Estimate System (I/B/E/S) and financial statement and financial market data from Compustat and CRSP, respectively, to determine stock price return and earnings surprises.

The sample period is 2005–2012. The authors extract all opinion articles published on SA during that time period and focus on 97,070 SA articles that concentrate on a single stock—roughly one-third of all articles published on SA. The authors build on the existing literature, which suggests that the frequency of negative words used in an article captures the tone of the report, with their textual analysis of articles and commentaries on SA. Moreover, to determine whether views expressed in SA articles and commentaries have more “value” than those expressed in traditional media outlets, they compare the effects of DJNS articles with those of SA articles.

Social media will increasingly displace traditional media and become the primary source of information for more people in the future. As such, the authors build on a growing body of research that analyzes the value of information on social media websites with respect to stock price return.