Please use this identifier to cite or link to this item: https://www.um.edu.mt/library/oar/handle/123456789/104044
Title: Investigating redundancy in emoji use : study on a twitter based corpus
Authors: Donato, Giulia
Paggio, Patrizia
Keywords: Social media -- Semiotics
Writing -- Interactive multimedia
Information retrieval
Natural language processing (Computer science)
Computational linguistics
Visual communication -- Digital techniques
Data mining
Emoticons -- Miscellanea
Issue Date: 2017
Publisher: The Association for Computational Linguistics
Citation: Donato, G., & Paggio, P. (2017, September). Investigating redundancy in emoji use: Study on a twitter based corpus. Proceedings of the 8th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis, 118-126. 
Abstract: In this paper we present an annotated corpus created with the aim of analyzing the informative behaviour of emoji – an issue of importance for sentiment analysis and natural language processing. The corpus consists of 2475 tweets all containing at least one emoji, which has been annotated using one of the three possible classes: Redundant, Non Redundant, and Non Redundant + POS. We explain how the corpus was collected, describe the annotation procedure and the interface developed for the task. We provide an analysis of the corpus, considering also possible predictive features, discuss the problematic aspects of the annotation, and suggest future improvements.
URI: https://www.um.edu.mt/library/oar/handle/123456789/104044
ISBN: 9781945626951
Appears in Collections:Scholarly Works - InsLin

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