research-article

Extracting and evaluating conversational patterns in social media

Authors:

José Emmanuel Ramirez MarquezAuthors Info & Claims

International Journal of Information Management: The Journal for Information Professionals, Volume 35, Issue 4

Pages 490 - 503

https://doi.org/10.1016/j.ijinfomgt.2015.04.001

Published: 01 August 2015 Publication History

Abstract

Reactions to new products by Apple and Samsung are assessed analyzing Twitter streams.Streams are modeled as virtual conversations, generating dynamically updated concept maps.Using topological analysis we identify patterns of what people say and how they talk.Apple conversation is less fragmented, contains more topics, and less negative sentiment. In this paper we use Twitter data to assess customers early reactions to the launch of two new products by Apple and Samsung by analyzing the streams generated in a 72h window around the two events. We present a methodology based on conversational analysis to extract concept maps from Twitter streams and use semantic and topological metrics to compare the conversations. Our findings show that there are significant differences in the structural patterns of the two conversations and that the analysis of these differences can be highly informative about early customers perceptions and value judgments associated with the competing products.

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cover image International Journal of Information Management: The Journal for Information Professionals

International Journal of Information Management: The Journal for Information Professionals Volume 35, Issue 4

August 2015

155 pages

ISSN:0268-4012

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Copyright © Elsevier Ltd.

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Elsevier Science Publishers B. V.

Netherlands

Publication History

Published: 01 August 2015

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Park SKim H(2024)Extracting product design guidance from online reviewsExpert Systems with Applications: An International Journal10.1016/j.eswa.2023.121357236:COnline publication date: 1-Feb-2024
https://dl.acm.org/doi/10.1016/j.eswa.2023.121357
Krishnan HElayidom MSanthanakrishnan T. (2022)A Comprehensive Survey on Sentiment Analysis in Twitter DataInternational Journal of Distributed Systems and Technologies10.4018/IJDST.30035213:5(1-22)Online publication date: 1-Jan-2022
https://dl.acm.org/doi/10.4018/IJDST.300352
Martí Bigorra AIsaksson OKarlberg M(2020)Semi-autonomous methodology to validate and update customer needs database through text data analyticsInternational Journal of Information Management: The Journal for Information Professionals10.1016/j.ijinfomgt.2020.10207352:COnline publication date: 1-Jun-2020
https://dl.acm.org/doi/10.1016/j.ijinfomgt.2020.102073
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