Twitter Permeability to financial events: an experiment towards a model for sensing irregularities
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- Feng Xiong & Kim MacKenzie, 2015. "The business use of Twitter by Australian listed companies," Journal of Developing Areas, Tennessee State University, College of Business, vol. 49(6), pages 421-428, Special I.
- Gregory S. Miller & Douglas J. Skinner, 2015. "The Evolving Disclosure Landscape: How Changes in Technology, the Media, and Capital Markets Are Affecting Disclosure," Journal of Accounting Research, Wiley Blackwell, vol. 53(2), pages 221-239, May.
- Ali Tafti & Ryan Zotti & Wolfgang Jank, 2016. "Real-Time Diffusion of Information on Twitter and the Financial Markets," PLOS ONE, Public Library of Science, vol. 11(8), pages 1-16, August.
- Gabriele Ranco & Darko Aleksovski & Guido Caldarelli & Miha Grčar & Igor Mozetič, 2015. "The Effects of Twitter Sentiment on Stock Price Returns," PLOS ONE, Public Library of Science, vol. 10(9), pages 1-21, September.
- Zheludev, Ilya & Smith, Robert & Aste, Tomaso, 2014. "When can social media lead financial markets?," LSE Research Online Documents on Economics 57376, London School of Economics and Political Science, LSE Library.
- Timm O. Sprenger & Andranik Tumasjan & Philipp G. Sandner & Isabell M. Welpe, 2014. "Tweets and Trades: the Information Content of Stock Microblogs," European Financial Management, European Financial Management Association, vol. 20(5), pages 926-957, November.
- Feng Xiong & Kim MacKenzie, 2015. "The business use of Twitter by Australian listed companies," Journal of Developing Areas, Tennessee State University, College of Business, vol. 49(5), pages 421-428, Special I.
- Billett, Matthew T. & Yu, Miaomiao, 2016. "Asymmetric Information, Financial Reporting, and Open-Market Share Repurchases," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 51(4), pages 1165-1192, August.
- Sanjiv Sabherwal & Salil K. Sarkar & Ying Zhang, 2011. "Do Internet Stock Message Boards Influence Trading? Evidence from Heavily Discussed Stocks with No Fundamental News," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 38(9-10), pages 1209-1237, November.
- Werner Antweiler & Murray Z. Frank, 2004. "Is All That Talk Just Noise? The Information Content of Internet Stock Message Boards," Journal of Finance, American Finance Association, vol. 59(3), pages 1259-1294, June.
- Bart Hobijn & Boyan Jovanovic, 2001.
"The Information-Technology Revolution and the Stock Market: Evidence,"
American Economic Review, American Economic Association, vol. 91(5), pages 1203-1220, December.
- Bart Hobijn & Boyan Jovanovic, 2000. "The Information Technology Revolution and the Stock Market: Evidence," NBER Working Papers 7684, National Bureau of Economic Research, Inc.
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This paper has been announced in the following NEP Reports:- NEP-EXP-2024-01-22 (Experimental Economics)
- NEP-PAY-2024-01-22 (Payment Systems and Financial Technology)
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