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 |
Files in This Item:
File | Description | Size | Format | |
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Investigating_redundancy_in_emoji_use_Study_on_a_twitter_based_corpus(2017).pdf | 209.96 kB | Adobe PDF | View/Open |
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