Optimising Agile Social Media Analysis

Thomas Kober, David Weir

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Agile social media analysis involves building bespoke, one-off classification pipelines tailored to the analysis of specific datasets. In this study we investigate how the DUALIST architecture can be optimised for agile social media analysis. We evaluate several semi-supervised learning algorithms in conjunction with a Naïve Bayes model, and show how these modifications can improve the performance of bespoke classifiers for a variety of tasks on a large range of datasets.
Original languageEnglish
Title of host publicationProceedings of the 6th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis
PublisherAssociation for Computational Linguistics
Pages31-40
Number of pages10
DOIs
Publication statusPublished - 2015
Event6th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis - Lisbon, Portugal
Duration: 17 Sep 2015 → …
https://wt-public.emm4u.eu/wassa2015/index.htm?opc=0

Workshop

Workshop6th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis
Abbreviated titleWASSA 2015
Country/TerritoryPortugal
CityLisbon
Period17/09/15 → …
Internet address

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