Towards the easy analysis of mass media audience reaction on social networks via discursive category tools

Stefanie Niklander, Ricardo Soto, Broderick Crawford

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

Abstract

The Mass Media involves information and communication products targeted to a wide audience. Today such communications products are also available on Internet where people can react to a given information by posting critics, congratulations, opinions or whatever they want via social networks. Such reactions are considered valuable information for instance to government and companies. However, this information is hard to automatically process as people commonly use ironies, stereotypes, metaphors expressed in informal writing plenty of chat abbreviations, emoticons, and slang words. In this paper, we illustrate how tools based on discursive categories can be used to analyze such reactions and thus to process and understand the information behind them.

Original languageEnglish
Title of host publicationHCI International 2015 - Posters Extended Abstracts - International Conference, HCI International 2015, Proceedings
EditorsConstantine Stephanidis
PublisherSpringer Verlag
Pages103-106
Number of pages4
ISBN (Print)9783319213828
DOIs
StatePublished - 2015
Externally publishedYes
Event17th International Conference on Human-Computer Interaction, HCI International 2015 - Los Angeles, United States
Duration: 2 Aug 20157 Aug 2015

Publication series

NameCommunications in Computer and Information Science
Volume529
ISSN (Print)1865-0929

Conference

Conference17th International Conference on Human-Computer Interaction, HCI International 2015
Country/TerritoryUnited States
CityLos Angeles
Period2/08/157/08/15

Keywords

  • Discourse category tools
  • Mass media
  • Social networks

Fingerprint

Dive into the research topics of 'Towards the easy analysis of mass media audience reaction on social networks via discursive category tools'. Together they form a unique fingerprint.

Cite this