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Tsinghua Science and Technology 2018, 23(1): 104-113 https://doi.org/10.26599/TST.2018.9010012
Open Access | Issue | Published: 15 February 2018

Influence Analysis of Emotional Behaviors and User Relationships Based on Twitter Data

Show Author's Information Kiichi Tago,  Qun Jin( )
Graduate School of Human Sciences, Waseda University, Tokorozawa 359-1192, Japan.
Keywords:
Twitter, social data analysis, emotional behavior, user relationship, Brunner–Munzel test
Cite this article:
Tago K, Jin Q. Influence Analysis of Emotional Behaviors and User Relationships Based on Twitter Data. Tsinghua Science and Technology, 2018, 23(1): 104-113. https://doi.org/10.26599/TST.2018.9010012
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Abstract Full text About this article

One of the main purposes for which people use Twitter is to share emotions with others. Users can easily post a message as a short text when they experience emotions such as pleasure or sadness. Such tweet serves to acquire empathy from followers, and can possibly influence others’ emotions. In this study, we analyze the influence of emotional behaviors to user relationships based on Twitter data using two dictionaries of emotional words. Emotion scores are calculated via keyword matching. Moreover, we design three experiments with different settings: calculate the average emotion score of a user with random sampling, calculate the average emotion score using all emotional tweets, and calculate the average emotion score using emotional tweets, excluding users of few emotional tweets. We evaluate the influence of emotional behaviors to user relationships through the Brunner–Munzel test. The result shows that a positive user is more active than a negative user in constructing user relationships in a specific condition.


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About this article

Influence Analysis of Emotional Behaviors and User Relationships Based on Twitter Data

Show Author's information Kiichi Tago, Qun Jin( )
Graduate School of Human Sciences, Waseda University, Tokorozawa 359-1192, Japan.

Abstract

One of the main purposes for which people use Twitter is to share emotions with others. Users can easily post a message as a short text when they experience emotions such as pleasure or sadness. Such tweet serves to acquire empathy from followers, and can possibly influence others’ emotions. In this study, we analyze the influence of emotional behaviors to user relationships based on Twitter data using two dictionaries of emotional words. Emotion scores are calculated via keyword matching. Moreover, we design three experiments with different settings: calculate the average emotion score of a user with random sampling, calculate the average emotion score using all emotional tweets, and calculate the average emotion score using emotional tweets, excluding users of few emotional tweets. We evaluate the influence of emotional behaviors to user relationships through the Brunner–Munzel test. The result shows that a positive user is more active than a negative user in constructing user relationships in a specific condition.

Keywords: Twitter, social data analysis, emotional behavior, user relationship, Brunner–Munzel test

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Received: 10 July 2017
Accepted: 04 September 2017
Published: 15 February 2018
Issue date: February 2018

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