Sentiment-based influence detection on TwitterReport as inadecuate




Sentiment-based influence detection on Twitter - Download this document for free, or read online. Document in PDF available to download.

Journal of the Brazilian Computer Society

, Volume 18, Issue 3, pp 169–183

First Online: 24 December 2011Received: 14 June 2011Accepted: 25 November 2011

Abstract

The user generated content available in online communities is easy to create and consume. Lately, it also became strategically important to companies interested in obtaining population feedback on products, merchandising, etc. One of the most important online communities is Twitter: recent statistics report 65 million new tweets each day. However, processing this amount of data is very costly and a big portion of the content is simply not useful for strategic analysis. Thus, in order to filter the data to be analyzed, we propose a new method for ranking the most influential users in Twitter. Our approach is based on a combination of the user position in networks that emerge from Twitter relations, the polarity of her opinions and the textual quality of her tweets. Our experimental evaluation shows that our approach can successfully identify some of the most influential users and that interactions between users provide the best evidence to determine user influence.

KeywordsTwitter User influence  Download to read the full article text



Author: Carolina Bigonha - Thiago N. C. Cardoso - Mirella M. Moro - Marcos A. Gonçalves - Virgílio A. F. Almeida

Source: https://link.springer.com/







Related documents