Semih Sevim

Work place: Kocaeli University Computer Engineering Departmen, Kocaeli, TURKEY

E-mail: semih.sevimm@gmail.com

Website:

Research Interests: Natural Language Processing, Data Mining, Data Structures and Algorithms

Biography

Semih Sevim is postgraduate at the Kocaeli University Computer Engineering Department in Turkey, interested in data mining, natural language processing and sentiment analysis.

Author Articles
An Ensemble Model using a BabelNet Enriched Document Space for Twitter Sentiment Classification

By Semih Sevim Sevinc ilhan Omurca Ekin Ekinci

DOI: https://doi.org/10.5815/ijitcs.2018.01.03, Pub. Date: 8 Jan. 2018

With the widespread usage of social media in our daily lives, user reviews emerged as an impactful factor for numerous fields including understanding consumer attitudes, determining political tendency, revealing strengths or weaknesses of many different organizations. Today, people are chatting with their friends, carrying out social relations, shopping and following many current events through the social media. However social media limits the size of user messages. The users generally express their opinions by using emoticons, abbreviations, slangs, and symbols instead of words. This situation makes the sentiment classification of social media texts more complex. In this paper a sentiment classification model for Twitter messages is proposed to overcome this difficulty. In the proposed model first the short messages are expanded with BabelNet which is a concept network. Then the expanded and the original form of the messages are included in an ensemble learning model. Consequently we compared our ensemble model with traditional classification algorithms and observed that the F-measure value is increased.

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