Abstract
The article introduces social network user sentiment evaluation with proposed technique based on fuzzy sets. The advantage of proposed technique consists in ability to take into account user's influence as well as the fact that a user could be an author of several messages. Results presented in this paper can be used in mechanical engineering to analyze reviews on products as well as in robotics for developing user communication interface. The paper contains experimental data and shows the steps of sentiment value calculation of resulting messages on a certain topic. Application of proposed technique is demonstrated on experimental data from Twitter social network.
Highlights
Today it has become common practice for people to use social networks to express opinions on topics of interest or to write reviews on used products and services
Results depicted in figure 6 allows for the conclusion that users' sentiments on the analyzed topic vary significantly: from negative value to a highly positive
The algorithm of message parsing for social network user sentiments evaluation was described in the paper
Summary
Today it has become common practice for people to use social networks to express opinions on topics of interest or to write reviews on used products and services. Analysis of related scientific papers on the subject of automated assessment of social network user sentiments [2,3,4,5,6] reveals that techniques proposed there do not take into account the relationship between users and limitations associated with the processing characteristics of linguistic hedges frequently occurred in messages. The object of this paper is to represent the algorithm of message parsing as well as the application of the method to experimental data from Twitter social network.
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