Authors: Nathalie De Marcellis-Warin; William Sanger; Thierry Warin
Addresses: Center for Interuniversity Research and Analysis of Organizations (CIRANO), 1130 Sherbrooke Ouest, #1400, Montréal (Québec) H3A 2M8, Canada; Department of Mathematics and Industrial Engineering, Polytechnique Montreal, P.O. Box 6079, Station Centre Ville, Montréal (Québec) H3C 3A7, Canada ' Department of Mathematics and Industrial Engineering, Polytechnique Montreal, P.O. Box 6079, Station Centre Ville, Montréal (Québec) H3C 3A7, Canada ' Department of International Business, HEC Montreal, 3000 chemin de la Côte Sainte Catherine, Montréal (Québec) H3T 2A7, Canada
Abstract: Assessing influence on social media is at the heart of a new trend in humanities and social sciences. Our paper is about assessing users' influence on social networks. We compare four different methods regarding tweets about financial conversations. We have built two datasets with respectively 489,000 and 280,000 financial tweets. While getting additional followers may provide insight of an increasing popularity, it does not necessarily translate into a more influential position. Our results suggest that the number of followers is only one element of what is considered to be influential. Indeed, the number of messages can be biased by what can be described as 'noisy' users. The number of retweets is a more refined proxy about influence. Finally, the betweenness centrality in the retweet network provides some privileged information to anyone following these users. We compare the performance of stocks mentioned by each type of users. From these results, such methods of assessing influence on Twitter leverage the acquisition of preferential signals in a financial context.
Keywords: Twitter; network analysis; retweet networks; data mining; financial conversations; influence.
International Journal of Web Based Communities, 2017 Vol.13 No.3, pp.281 - 310
Received: 28 Mar 2016
Accepted: 21 Nov 2016
Published online: 04 Sep 2017 *