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Web"],"published-print":{"date-parts":[[2019,5,31]]},"abstract":"<jats:p>\n            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 been systematically investigated before. Here, we study 9M tweets related to stocks of the five 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\u2014referred to as\n            <jats:italic>cashtag piggybacking<\/jats:italic>\n            \u2014perpetrated by coordinated groups of bots and likely aimed at promoting low-value stocks by exploiting the popularity of high-value ones. Among the findings of our study is that as much as 71% of the authors of suspicious financial tweets are classified as bots by a state-of-the-art spambot-detection algorithm. Furthermore, 37% of them were suspended by Twitter a few months after our investigation. 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.\n          <\/jats:p>","DOI":"10.1145\/3313184","type":"journal-article","created":{"date-parts":[[2019,4,4]],"date-time":"2019-04-04T18:38:37Z","timestamp":1554403117000},"page":"1-27","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":99,"title":["Cashtag Piggybacking"],"prefix":"10.1145","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0170-2445","authenticated-orcid":false,"given":"Stefano","family":"Cresci","sequence":"first","affiliation":[{"name":"Institute of Informatics and Telematics, IIT-CNR, Pisa, Italy"}]},{"given":"Fabrizio","family":"Lillo","sequence":"additional","affiliation":[{"name":"Department of Mathematics, University of Bologna, Italy and Scuola Normale Superiore of Pisa, Bologna, Italy"}]},{"given":"Daniele","family":"Regoli","sequence":"additional","affiliation":[{"name":"Azimut Analytics srl, Milano, Italy and Scuola Normale Superiore of Pisa, Milano, Italy"}]},{"given":"Serena","family":"Tardelli","sequence":"additional","affiliation":[{"name":"Institute of Informatics and Telematics, IIT-CNR, Pisa, Italy"}]},{"given":"Maurizio","family":"Tesconi","sequence":"additional","affiliation":[{"name":"Institute of Informatics and Telematics, IIT-CNR, Pisa, Italy"}]}],"member":"320","published-online":{"date-parts":[[2019,4,3]]},"reference":[{"key":"e_1_2_2_1_1","volume-title":"Proceedings of the 6th International Conference on Web and Social Media (ICWSM\u201912)","author":"Aiello Luca Maria","year":"2012","unstructured":"Luca Maria Aiello , Martina Deplano , Rossano Schifanella , and Giancarlo Ruffo . 2012 . 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