%0 Conference Proceedings
%T Mining and Estimating Users’ Opinion Strength in Forum Texts Regarding Governmental Decisions
%+ Department of Applications of Information Technology in Administration and Economy [Lefkada]
%+ Department of Computer Engineering and Informatics [Patras]
%A Stylios, George
%A Tsolis, Dimitrios
%A Christodoulakis, Dimitrios
%Z Part 7: First Mining Humanistic Data Workshop (MHDW 2012)
%< avec comité de lecture
%( IFIP Advances in Information and Communication Technology
%B 8th International Conference on Artificial Intelligence Applications and Innovations (AIAI)
%C Halkidiki, Greece
%Y Lazaros Iliadis
%Y Ilias Maglogiannis
%Y Harris Papadopoulos
%Y Kostas Karatzas
%Y Spyros Sioutas
%I Springer
%3 Artificial Intelligence Applications and Innovations
%V AICT-382
%N Part II
%P 451-459
%8 2012-09-27
%D 2012
%R 10.1007/978-3-642-33412-2_46
%K Opinion mining
%K opinion strength mining
%K sentiment analysis
%K E-Government
%K Knowledge extraction
%K linguistic analysis
%K Machine learning
%K Support Vector Machines
%Z Computer Science [cs]Conference papers
%X Web 2.0 has facilitated interactive information sharing on the WWW, allowing users the opportunity to articulate their opinions on different topics. In this framework, certain practices implement information monitoring systems so as digests, reports on keywords and thematic queries regarding opinions on government decisions to be created. Analysis of rubrics associations, primary semantic and statistical interpretation of the texts is usually carried out. It is, on the other hand, rather difficult to get punctual predicts and estimate sufficiently forum users’ opinion strength. In this work we present a methodology which automatically mines and estimates the strength of users’ opinions on text forums regarding government decisions. According to our methodology, quantitative features are automatically mined from forum posts and then passed to a Support Vector Machine based classifier where the users’ opinion strength is estimated. The proposed methodology has been validated in real data and initial experimental results are presented.
%G English
%Z TC 12
%Z WG 12.5
%2 https://hal.science/hal-01523037/document
%2 https://hal.science/hal-01523037/file/978-3-642-33412-2_46_Chapter.pdf
%L hal-01523037
%U https://hal.science/hal-01523037
%~ IFIP
%~ IFIP-AICT
%~ IFIP-TC
%~ IFIP-WG
%~ IFIP-TC12
%~ IFIP-AIAI
%~ IFIP-WG12-5
%~ IFIP-AICT-382
%~ TEST3-HALCNRS