Title :
Sentiment-based text segmentation
Author :
Chiru, Costin-Gabriel ; Hadgu, Asmelash Teka
Author_Institution :
Dept. of Comput. Sci. & Eng., Politeh. Univ. of Bucharest, Bucharest, Romania
Abstract :
In this paper, we present a text segmentation system based on the sentiments expressed in the text. The system takes as input plain text (product review for instance) and uses two different resources for tagging the sentiment words: a sentiment words dictionary and SentiWordNet. Once the sentiment words are identified, the initial text is annotated with segmentation markers when polarity shifts. The system also outputs the counts of positive and negative sentiment words found in text and optionally annotates them with their valence.
Keywords :
dictionaries; information retrieval; social networking (online); text analysis; word processing; SentiWordNet; negative sentiment words; plain text; polarity shifts; positive sentiment words; segmentation markers; sentiment word dictionary; sentiment word identification; sentiment word tagging; sentiment-based text segmentation; text annotation; Batteries; Dictionaries; Digital cameras; Feature extraction; Tagging; Warranties; Parsing; Products Evaluation Based on Social Media; Sentiments Analysis; Tagging; Text Segmentation;
Conference_Titel :
Systems and Computer Science (ICSCS), 2013 2nd International Conference on
Conference_Location :
Villeneuve d´Ascq
Print_ISBN :
978-1-4799-2020-4
DOI :
10.1109/IcConSCS.2013.6632053