Hussam Hamdan


2017

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Senti17 at SemEval-2017 Task 4: Ten Convolutional Neural Network Voters for Tweet Polarity Classification
Hussam Hamdan
Proceedings of the 11th International Workshop on Semantic Evaluation (SemEval-2017)

This paper presents Senti17 system which uses ten convolutional neural networks (ConvNet) to assign a sentiment label to a tweet. The network consists of a convolutional layer followed by a fully-connected layer and a Softmax on top. Ten instances of this network are initialized with the same word embeddings as inputs but with different initializations for the network weights. We combine the results of all instances by selecting the sentiment label given by the majority of the ten voters. This system is ranked fourth in SemEval-2017 Task4 over 38 systems with 67.4% average recall.

2016

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SentiSys at SemEval-2016 Task 4: Feature-Based System for Sentiment Analysis in Twitter
Hussam Hamdan
Proceedings of the 10th International Workshop on Semantic Evaluation (SemEval-2016)

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SentiSys at SemEval-2016 Task 5: Opinion Target Extraction and Sentiment Polarity Detection
Hussam Hamdan
Proceedings of the 10th International Workshop on Semantic Evaluation (SemEval-2016)

2015

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Lsislif: Feature Extraction and Label Weighting for Sentiment Analysis in Twitter
Hussam Hamdan | Patrice Bellot | Frederic Bechet
Proceedings of the 9th International Workshop on Semantic Evaluation (SemEval 2015)

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Lsislif: CRF and Logistic Regression for Opinion Target Extraction and Sentiment Polarity Analysis
Hussam Hamdan | Patrice Bellot | Frederic Bechet
Proceedings of the 9th International Workshop on Semantic Evaluation (SemEval 2015)

2014

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A Collection of Scholarly Book Reviews from the Platforms of electronic sources in Humanities and Social Sciences OpenEdition.org
Chahinez Benkoussas | Hussam Hamdan | Patrice Bellot | Frédéric Béchet | Elodie Faath
Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14)

In this paper, we present our contribution for the automatic construction of the Scholarly Book Reviews corpora from two different sources, the OpenEdition platform which is dedicated to electronic resources in the humanities and social sciences, and the Web. The main target is the collect of reviews in order to provide automatic links between each review and its potential book in the future. For these purposes, we propose different document representations and we apply some supervised approaches for binary genre classification before evaluating their impact.

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Supervised Methods for Aspect-Based Sentiment Analysis
Hussam Hamdan | Patrice Bellot | Frederic Béchet
Proceedings of the 8th International Workshop on Semantic Evaluation (SemEval 2014)

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The Impact of Z_score on Twitter Sentiment Analysis
Hussam Hamdan | Patrice Bellot | Frederic Béchet
Proceedings of the 8th International Workshop on Semantic Evaluation (SemEval 2014)

2013

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Experiments with DBpedia, WordNet and SentiWordNet as resources for sentiment analysis in micro-blogging
Hussam Hamdan | Frederic Béchet | Patrice Bellot
Second Joint Conference on Lexical and Computational Semantics (*SEM), Volume 2: Proceedings of the Seventh International Workshop on Semantic Evaluation (SemEval 2013)