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$FAKE: Evidence of spam and bot activity in stock microblogs on Twitter

Microblogs are increasingly exploited for predicting prices and traded volumes of stocks in financial markets. However, it has been demonstrated that much of the content shared in microblogging platforms is created and publicized by bots and spammers. Yet, the presence (or lack thereof) and the impact of fake stock microblogs has never systematically been investigated before. Here, we study 9M tweets related to stocks of the 5 main financial markets in the US. By comparing tweets with financial data from Google Finance, we highlight important characteristics of Twitter stock microblogs. More importantly, we uncover a malicious practice perpetrated by coordinated groups of bots and likely aimed at promoting low-value stocks by exploiting the popularity of high-value ones. Our results call for the adoption of spam and bot detection techniques in all studies and applications that exploit user-generated content for predicting the stock market.
The 12th International AAAI Conference on Web and Social Media (ICWSM'18), Stanford, California, USA, 2018

Autori esterni: Fabrizio Lillo (Dipartimento di Matematica, Università di Bologna), Daniele Regoli (Scuola Normale Superiore, Pisa)
Autori IIT:

Serena Tardelli

Foto di Serena Tardelli

Tipo: Contributo in atti di convegno
Area di disciplina: Computer Science & Engineering

File: ICWSM-18_paper_292_short.pdf

Attività: Social Media Analysis