The Effects of Twitter Sentiment on Stock Price Returns

Ranco, Gabriele; Aleksovski, Darko; Caldarelli, Guido; Grčar, Miha; Mozetič, Igor

doi:10.1371/journal.pone.0138441

Cited by 277 publications

(205 citation statements)

References 57 publications

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“…Naive Bayes or Support Vector Machines) are applied to extract sentiment based on supervised learning (i.e. a labeled/ annotated training data set are required to build this classification model).Yet, the manual annotation and cross-validation of this data set that are required to obtain reliable labeled tweets is highly expensive and time-consuming (Ranco, Aleksovski, Caldarelli, Grcar, & Mozetic, 2015;Oliveira et al, 2017).…”

Section: Methodsological Considerationsmentioning

confidence: 99%

“…In a similar study, Ranco et al (2015) examine the relationship between Twitter activity and sentiment and stock returns for a sample of the 30 constituent firms of the Dow Jones Industrial Average (DJIA) index. The sample used consists of 1.5 million tweets collected about the sample firms during the period (2013)(2014).…”

Section: Twitter Sentiment/information and Stock Market Performancementioning

confidence: 99%

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Twitter, Investor Sentiment and Capital Markets: What Do We Know?

Ali¹

2018

IJEF

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Nowadays, the social media play a central role not only in "de-asymmetrizing" the information between firms and investors but also in influencing the emotional response to this information. The social media have provided firms with the opportunity to construct their image and stimulate significant attention and positive emotional responses (i.e. celebrity firm). Investors also become no longer passive participants; they can now communicate, re-tweet, comment, mention, react to information and express their sentiment/views. Theoretically, this should exert a positive impact on information diffusion and so the market efficiency. However, as the social media also significantly influence the public mood and emotional response to any new information/news, several behavioral explanations contradicting with the concept of market efficiency (e.g. investor sentiment and herding behavior) become more reasonable. The study aims at providing a literature review and synthesis of research on the impact of social media sentiment in the context of capital markets, scrutinizing the theoretical understanding of this impact, underlining the methodological challenges related to extracting the sentiment, and reviewing the main empirical findings on the impact in the context of Twitter and StockTwits, which will enable researchers to evaluate and classify existing studies, obtain useful insight into the theoretical understanding of the impact of social media sentiment, hence spurring further theoretical and empirical research.

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Section: Methodsological Considerationsmentioning

confidence: 99%

Section: Twitter Sentiment/information and Stock Market Performancementioning

confidence: 99%

Twitter, Investor Sentiment and Capital Markets: What Do We Know?

Ali¹

2018

IJEF

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“…For instance, [42] investigated a 15-month period of Twitter data including sentiment, concerning 30 stock companies registered on the Dow Jones Industrial Average (DJIA) index. This work gave some insights about sentiment and abnormal returns during the peaks of Twitter volume.…”

Section: Twitter As a Source For Decision Makingmentioning

confidence: 99%

Twitter permeability to financial events: an experiment towards a model for sensing irregularities

Vilas

Redondo

Crockett

et al. 2018

Multimed Tools Appl

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There is a general consensus of the good sensing and novelty characteristics of Twitter as an information media for the complex financial market. This paper investigates the permeability of Twittersphere, the total universe of Twitter users and their habits, towards relevant events in the financial market. Analysis shows that a general purpose social media is permeable to financial-specific events and establishes Twitter as a relevant feeder for taking decisions regarding the financial market and event fraudulent activities in that market. However, the provenance of contributions, their different levels of credibility and quality and even the purpose or intention behind them should to be considered and carefully contemplated if Twitter is used as a single source for decision taking. With the overall aim of this research, to deploy an architecture for real-time monitoring of irregularities in the financial market, this paper conducts a series of experiments on the level of permeability and the permeable features of Twitter in the event of one of these irregularities. To be precise, Twitter data is collected concerning an event comprising of a specific financial action on the 27th January 2017: the announcement about the merge of two companies Tesco PLC and Booker Group PLC, listed in the main market of the London Stock Exchange

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“…Still, other forms of high-speed financial analysis are disrupting and transforming the marketplace. Firms like Neokami and Sentient now offer trading platforms using Big Data analytics that not only cover unusual order flow but, also, company reports, conference calls, and the sentiment and mood analysis of social media messages (Barberis, Shleifer, and Vishny, 1998;Brown & Cliff, 2004;Tetlock, 2007;Antweiler & Frank, 2004;Wurgler, 2007;Zhang, Fuehres, and Gloor, 2011;Kleinnijenhuis, Schultz, Oegema, and Van Atteveldt, 2013;Lee, Hutton, and Shu, 2015;Ranco, Aleksovski, Caldarelli, Grčar, and Mozetič, 2015). "We can analyze millions of variables within seconds and create a customized predictive model for any stock," says Ozel Christo, founder and CEO of Neokami.…”

Section: Big Data Analytics and Social Media Feedsmentioning

confidence: 99%

Is Financial Analysis Doomed? The Birth of “Reactive Valuation” Analysis

Griffin¹,

Padaria²

2017

AFR

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The purpose of this paper is to examine how firms' information landscape has changed in recent years and why this could be problematic for those engaged in financial analysis and equity valuation. Our central contention is that two main forces of change -lower information costs and faster information processing -have completely disrupted the traditional concept of financial analysis. In response to this disruption, financial analysis will now increasingly take the form of "reactive valuation." In addition to examining our main contention, we introduce a new term into the literature, called "reactive valuation," which we define as the ultra short-term valuation of an equity, lasting from a few seconds to a few hours, based on information primarily published through social media channels. It may be later corroborated by factually based information or remain unsubstantiated. It may or may not be from an authoritative source. It also may not relate clearly or directly to the valuation of the underlying asset. However, based mostly on the tools of artificial intelligence and natural language processing, "reactive valuation" will invariably provide an opportunity for statistical arbitrage during the short time it takes for the market to digest the information. Financial analysts who survive these two forces of change will have detailed knowledge of this new form of financial analysis.

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The Effects of Twitter Sentiment on Stock Price Returns

Cited by 277 publications

References 57 publications

Twitter, Investor Sentiment and Capital Markets: What Do We Know?

Twitter, Investor Sentiment and Capital Markets: What Do We Know?

Twitter permeability to financial events: an experiment towards a model for sensing irregularities

Is Financial Analysis Doomed? The Birth of “Reactive Valuation” Analysis

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