Computer Engineering / Bilgisayar Mühendisliği
Permanent URI for this collectionhttps://hdl.handle.net/11147/10
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Conference Object Citation - Scopus: 3Ontology Supported Policy Modeling in Opinion Mining Process(Springer Verlag, 2012) Husaini, Mus'ab; Ko, Andrea; Tapucu, Dilek; Saygın, YücelIn e-Society the spreading services offered by Social Web has changed the way of communication and cooperation among citizens, policy-makers, governance bodies and civil society actors. One of the main goals of policymakers is to motivate citizens for participation in policy-making processes. UbiPOL ((Ubiquitous Participation Platform for Policy-making, ICT-2009.7.3(ICT for Governance and Policy Modelling), 2009-2011) aimed to develop a ubiquitous solution, which emphasizes citizens' participation in policy-making processes (PMPs) regardless of their current location and time. Ontology-based opinion mining component of Ubipol system has a crucial role in citizens' commitment, because it empowers them to contribute in policy making. This paper presents the ontology-based semi-automatic approach and tool for sentiment analysis in Ubipol system, which include lexicon extraction from a large corpus of documents. Aspect-based opinion summarization of user reviews and its combination with domain ontology development are discussed as well.Conference Object Citation - WoS: 1Citation - Scopus: 1A Relativistic Opinion Mining Approach To Detect Factual or Opinionated News Sources(Springer Verlag, 2017) Sezerer, Erhan; Tekir, SelmaThe credibility of news cannot be isolated from that of its source. Further, it is mainly associated with a news source’s trustworthiness and expertise. In an effort to measure the trustworthiness of a news source, the factor of “is factual or opinionated” must be considered among others. In this work, we propose an unsupervised probabilistic lexicon-based opinion mining approach to describe a news source as “being factual or opinionated”. We get words’ positive, negative, and objective scores from a sentiment lexicon and normalize these scores through the use of their cumulative distribution. The idea behind the use of such a statistical approach is inspired from the relativism that each word is evaluated with its difference from the average word. In order to test the effectiveness of the approach, three different news sources are chosen. They are editorials, New York Times articles, and Reuters articles, which differ in their characteristic of being opinionated. Thus, the experimental validation is done by the analysis of variance on these different groups of news. The results prove that our technique can distinguish the news articles from these groups with respect to “being factual or opinionated” in a statistically significant way.