Microblogging Metrics and Stock Return Comovement

Journal of Information Technology, 2017

Scholars and practitioners alike increasingly recognize the importance of stock microblogs as they capture the market discussion and have predictive value for financial markets. This paper examines the extent to which stock microblog messages are related to financial market indicators and the mechanism leading to efficient aggregation of information. In particular, this paper investigates the information content of stock microblogs with respect to individual stocks and explores the effects of social influences on an interday and intraday basis. We collected more than 1.2 million stock-related messages (i.e., tweets) related to S&P 100 companies over a period of 7 months. Using methods from computational linguistics, we went through an elaborate process of message feature reduction, spam detection, language detection, and slang removal, which has led to an increase in classification accuracy for sentiment analysis. We analyzed the data on both a daily and a 15-min basis and found tha...

Proceedings of the fifth ACM international conference on Web search and data mining - WSDM '12, 2012

We study the problem of correlating micro-blogging activity with stock-market events, defined as changes in the price and traded volume of stocks. Specifically, we collect messages related to a number of companies, and we search for correlations between stock-market events for those companies and features extracted from the microblogging messages. The features we extract can be categorized in two groups. Features in the first group measure the overall activity in the micro-blogging platform, such as number of posts, number of re-posts, and so on. Features in the second group measure properties of an induced interaction graph, for instance, the number of connected components, statistics on the degree distribution, and other graph-based properties.

Proceedings of the 5th Global Conference on Business, Management and Entrepreneurship (GCBME 2020), 2021

The purpose of this paper is to review microblogging sentiment investors on a literature-based. Focusing on defining and measuring online sentiment investors and understanding their impact on financial market behavior-using scholarly articles to analyze, define, and measure microblogging sentiment investors. All the articles have been classified to measure and underpinnings online investor sentiment theory and other determinants in psychological measure. We have used citation and bibliographic coupling analysis to provide a structure of microblogging sentiment investors. This research also investigates how microblogging forums have become an online platform for exchanging stock information among investors. This paper's result defines investor sentiment research development will further reveal new ways of measuring investor sentiment through big data social media on microblogging sentiment investors construct by identifying authors, cite, references, or keywords.

International Review of Economics & Finance, 2019

Social media has reshaped business models, economies, politics, and culture around the world. In this paper, we identified social media stocks from various sectors by using a strict, academic definition and then studied their performance and return characteristics. Multivariate regression results demonstrate that being recognized as a social media firm yields extra return. The performance of social media stocks is not associated with macrolevel sentiment, but rather with firm-level attention paid by potential investors. Causality tests indicate that the default risk premium and volatility have incremental power in explaining the performance of social media stocks.

 Abstract— Stocks are tweeted by investors and are traded in the markets with a potential interplay between daily stock price movements and social media content. We use four daily time-series variables: stock return, volatility, liquidity, and the volume of tweets to study the interdependences and comovements of social media content and stock performance. We find that the Granger causality relationship between the stock liquidity and the volume of tweets over stocks.

Anduli

The announcement of a certain event taking place may be important and impactful with regard to the stock market and share prices, even more than the effectiveness and significance of the event itself. The aim of this study is to analyze the effect of financial event announcements via social media, specifically Twitter, on share returns of stocks on the Financial Times Stock Exchange 100 Index. Our research questions were tested on a sample of 833 event observations retrieved from official Twitter accounts for two years (1 January 2014-16 February 2016). The test was concerned with tracking stock return behavior on the event day (day 0), the pre-event window and the post-event window using the event-study methodology. This study found that there is a significant relationship between share prices and the events announced via Twitter, the type of tweets, news categories and tweeting intensity of the company involved. Classifying based on the industry of the announcing company had no significant relationship to stock return behavior.

Global Social Sciences Review

In the online environment, social media metrics offer a credible basis of customer feedback in anticipating the firm performance. This study verifies the association of social media metrics of Face-book and Twitter to financial market performance. Data were collected from official Facebook pages and Twitter accounts of 3 fast-food companies over the time period of 6 months. Then established multiple metrics for respective social media platforms and develop outcomes using Vector Autoregressive time series models to evaluate the instantaneous and continuing relationship between social media metrics and financial market performance of the firms in terms of unusual returns and idiosyncratic risk. Results indicated that FB metrics are significant leading indicators of firm equity value. However, Twitter metrics, have a weaker relationship with firm value as compared to FB metrics. Collectively, current research extends new visions for organizational top executives and investors concernin...

Handbook of Social Media Management, 2012

Today, social media are emerging as a new platform for information exchange, discussions, and as a source of news. Many companies utilize social media platforms as marketing tools or for promotional purposes as a part of a marketing mix. Today, also online brokers provide online discussion forums, blogs, networking tools, educational material, or networking platforms as part of their marketing mix in order to directly reach the end consumer. Thus, today, social networks provide a pool of collaborative knowledge, which also allows the understanding of collaborative pricing behavior on stock markets. This includes e.g. specialized platforms providing collaborative knowledge around the topic of stock exchange trading via blogs, wikis, or communities. It's obvious that social media therefore provide insights into market sentiments and investing behavior, due to the collaborative knowledge and 'shared mind' of many investors. Social media therefore might act as a market sentiment indicator far beyond the currently existing sentiments based e.g. on questionnaires or quantitative consumer spending indexes. The analysis of the content can provide more insights into behavioral finance on stock markets and might lead to more real-time and accurate sentiments. Existing examples show the relation e.g. between discussions on social media and movie sales. It's obvious that social media based sentiment analysis provides new insights into the relation between stock exchange pricing and investors' sentiments and eventually into new behavior financing models. Example services, as e.g. StockTwits demonstrate the efficiency of social media as a tool (StockTwits, n.d.).

The investigation’s main objective is to examine the relationship between linguistic tone in Twitter messages posted by corporations and financial analysts, and abnormal stock returns

Journal of Asian Finance, Economics and Business, 2021

The covid-19 pandemic scenario caused the most extensive economic shocks the world has experienced in decades Maintaining financial performance and economic stability is essential during the pandemic period In these conditions, where movement is severely restricted, media consumption is considered to be increasing The social media platform is one of the media online used by the public as a source of information and also expressing their sentiment, including individual investors in the capital market as social media users Twitter is one of the social media microblogging platforms used by individual investors to share their opinion and get information This study aims to determine whether microblogging sentiment investors can predict the capital market during pandemics To analyze microblogging sentiment investors, we classified sentiment using the phyton text mining algorithm and Naive Bayesian text classification into level positive, negative, and neutral from November 2019 to Novembe...