Target-Dependent Sentiment Analysis of Tweets

Entity: Universitat Rovira i Virgili (URV)

Confidenciality: No

Education area(s): Enginyeria de la Seguretat Informàtica i Intel·ligència Artificial

Title in different languages: Target-Dependent Sentiment Analysis of Tweets

Abstract: TFM Summary: The task of target-dependent sentiment analysis aims to identify the sentiment polarity towards a certain target in a given text. All the existing models of this task assume that the target is known. This fact has motivated us to develop an end-to-end target-dependent sentiment analysis system. To the extent of our knowledge, this is the first system that identifies and extract the target of the tweets. The proposed system is composed of two main steps. First, the targets of the tweet to be analizad are extracted. Afterwards, the system identifies the polarities of the tweet towards each extracted target. We have evaluated the effectiveness of the proposed model on a benchmark dataset from Twitter. The experiments show that our proposed system outperforms the state-of-the-art methods for target-dependent sentiment analysis.

Subject: Enginyeria informàtica

Academic year: 2016-2017

Language: Anglès

Work's public defense date: 2017-06-09

Subject areas: Computer engineering

Student: Fadi Abdulfattah Mohammed Hassan

Work's codirector: Jabreel, Mohammed

Department: Enginyeria Informàtica i Matemàtiques

TFM credits: 9

Creation date in repository: 2017-09-28

Keywords: Deep Learning, Target Identification, Sentiment Analysis

Title in original language: Target-Dependent Sentiment Analysis of Tweets

Project director: Moreno, Antonio