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2015 | OriginalPaper | Buchkapitel

MultiSpot: Spotting Sentiments with Semantic Aware Multilevel Cascaded Analysis

verfasst von : Despoina Chatzakou, Nikolaos Passalis, Athena Vakali

Erschienen in: Big Data Analytics and Knowledge Discovery

Verlag: Springer International Publishing

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Abstract

Given a textual resource (e.g. post, review, comment), how can we spot the expressed sentiment? What will be the core information to be used for accurately capturing sentiment given a number of textual resources? Here, we introduce an approach for extracting and aggregating information from different text-levels, namely words and sentences, in an effort to improve the capturing of documents’ sentiments in relation to the state of the art approaches. Our main contributions are: (a) the proposal of two semantic aware approaches for enhancing the cascaded phase of a sentiment analysis process; and (b) MultiSpot, a multilevel sentiment analysis approach which combines word and sentence level features. We present experiments on two real-world datasets containing movie reviews.

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Titel: MultiSpot: Spotting Sentiments with Semantic Aware Multilevel Cascaded Analysis
verfasst von: Despoina Chatzakou
Nikolaos Passalis
Athena Vakali
Verlag: Springer International Publishing
Buch: Big Data Analytics and Knowledge Discovery
Print ISBN: 978-3-319-22728-3

Electronic ISBN: 978-3-319-22729-0

Copyright-Jahr: 2015
DOI: https://doi.org/10.1007/978-3-319-22729-0_26

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