Evaluation of social network user sentiments based on fuzzy sets; IOP Conference Series: Materials Science and Engineering; Vol. 93: Modern Technique and Technologies (MTT'2015)

Bibliographische Detailangaben
Parent link:IOP Conference Series: Materials Science and Engineering
Vol. 93: Modern Technique and Technologies (MTT'2015).— 2015.— [012054, 6 p.]
1. Verfasser: Luneva E. E. Elena Evgenievna
Körperschaft: Томский политехнический университет Институт кибернетики, ИК
Weitere Verfasser: Banokin P. I. Pavel Ivanovich, Efremov A. A. Aleksandr Aleksandrovich
Zusammenfassung:Title screen
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.
Режим доступа: по договору с организацией-держателем ресурса
Sprache:Englisch
Veröffentlicht: 2015
Schriftenreihe:Control science and system engineering
Schlagworte:
Online-Zugang:http://dx.doi.org/10.1088/1757-899X/93/1/012054
http://earchive.tpu.ru/handle/11683/20072
Format: Elektronisch Buchkapitel
KOHA link:https://koha.lib.tpu.ru/cgi-bin/koha/opac-detail.pl?biblionumber=644554

MARC

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330 |a 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. 
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