Intent classification of social media texts with machine learning for customer service improvement

Sebastián Pérez-Vera, Rodrigo Alfaro, Héctor Allende-Cid

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations

Abstract

Social media platforms in the last few years have facilitated the development of communities that discuss real-world events, and have shaped the way users interact. The content generated in these platforms reflect a variety of intentions, ranging from social interaction to commercial interest, among many others. The present study aims at the implementation of an automatic intent classification system for a Chilean electricity company social media account. The dataset was created from 5000 tweets that were manually classified by 5 people. If discrepancies were detected, a majority voting scheme was used in order to tag the tweets’ intentions. In order to perform the experimental validation of the automatic classification with the machine learning algorithms, several text representations were used (tf-idf, tf-rfl and bin-rfl). The results obtained from the various tests that were conducted yielded satisfactory results. We also analyzed how to assign automatic responses to frequently asked questions, and obtained promising results.

Original languageEnglish
Title of host publicationSocial Computing and Social Media
Subtitle of host publicationApplications and Analytics - 9th International Conference, SCSM 2017 Held as Part of HCI International 2017, Proceedings
EditorsGabriele Meiselwitz
PublisherSpringer Verlag
Pages258-274
Number of pages17
ISBN (Print)9783319585611
DOIs
StatePublished - 2017
Externally publishedYes
Event9th International Conference on Social Computing and Social Media, SCSM 2017, held as part of the 19th International Conference on Human-Computer Interaction, HCI 2017 - Vancouver, Canada
Duration: 9 Jul 201714 Jul 2017

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10283 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference9th International Conference on Social Computing and Social Media, SCSM 2017, held as part of the 19th International Conference on Human-Computer Interaction, HCI 2017
Country/TerritoryCanada
CityVancouver
Period9/07/1714/07/17

Keywords

  • Intent classification
  • Machine learning
  • Social media

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