Abstract
Twitter is a free social media service that allows anyone to say almost anything to anybody in 140 characters or less. Over the past few months, Twitter has experienced an explosive growth which has aroused the interest of many developers. In consequence, there have appeared many analytic tools which, besides other characteristics, calculate how influential a user is. This meaningful value can be estimated using different metrics and tools. In this paper, we study the reliability of them and show how data mining techniques can help: (a) to identify the actions which can increase the influence of a user (depending on the concrete tool), (b) to discover if those actions are related to different tools (and whether we can increase influence in more than one way), and (c) to advise people (or companies) about how they can get a greater impact.
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del Campo-Ávila, J., Moreno-Vergara, N., Trella-López, M. (2011). Analizying Factors to Increase the Influence of a Twitter User. In: Pérez, J.B., et al. Highlights in Practical Applications of Agents and Multiagent Systems. Advances in Intelligent and Soft Computing, vol 89. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-19917-2_9
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DOI: https://doi.org/10.1007/978-3-642-19917-2_9
Publisher Name: Springer, Berlin, Heidelberg
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