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Deep Tweets: from Entity Linking to Sentiment Analysis

Pierpaolo Basile 1 Valerio Basile 2 Malvina Nissim 3 Nicole Novielli 1
2 WIMMICS - Web-Instrumented Man-Machine Interactions, Communities and Semantics
CRISAM - Inria Sophia Antipolis - Méditerranée , Laboratoire I3S - SPARKS - Scalable and Pervasive softwARe and Knowledge Systems
Abstract : The huge amount of information streaming from online social networking is increasingly attracting the interest of researchers on sentiment analysis on micro-blogging platforms. We provide an overview on the open challenges of sentiment analysis on Italian tweets. We discuss methodological issues as well as new directions for investigation with particular focus on sentiment analysis of tweets containing figurative language and entity-based sentiment analysis of micro-posts.
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Submitted on : Wednesday, July 6, 2016 - 9:19:25 AM
Last modification on : Tuesday, December 7, 2021 - 4:10:18 PM


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  • HAL Id : hal-01342435, version 1



Pierpaolo Basile, Valerio Basile, Malvina Nissim, Nicole Novielli. Deep Tweets: from Entity Linking to Sentiment Analysis. Proceedings of the Italian Computational Linguistics Conference (CLiC-it 2015), Dec 2015, Trento, Italy. ⟨hal-01342435⟩



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