Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Twitter as the Second Channel
Linköping University, Department of Computer and Information Science. Linköping University, The Institute of Technology.
Linköping University, Department of Computer and Information Science. Linköping University, The Institute of Technology.
2014 (English)Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
Abstract [en]

People share a big part of their lives and opinions on platforms such as Facebook and Twitter. The companies behind these sites do their absolute best to collect as much data as possible. This data could be used to extract opinions in many different ways.

Every company, organization or public person is probably curious on what is being said about them right now. There are also areas where opinions are related to the outcome of an event. Examples of such events are presidential elections or the Eurovision Song Contest. In these events, peoples’ votes will directly reflect the outcome of the elections or contests.

We have developed a simplistic prototype that is able to predict the result of the Eurovision Song Contest using sentiment analysis on tweets. The prototype collects tweets about the event, performs sentiment analysis, and uses different filters to predict the ranks of the contestants. We evaluted our results with the actual voting results of the event and found a Pearson correlation of approximately 0.65.

With more time and resources we believe that it is possible to create a highly accurate prediction model. It could be used in lots of different contexts. Politicians and their parties could use it to evaluate their campaigns. The press could use it to create more interesting news reports. Companies would be able to investigate their brand appreciation. A system like this could be used in many different fields.

Place, publisher, year, edition, pages
2014. , 30 p.
Keyword [en]
twitter, predictions, eurovision, eurovision song contest, semantic analysis
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:liu:diva-110877ISRN: LIU-IDA/LITH-EX-G--14/063--SEOAI: oai:DiVA.org:liu-110877DiVA: diva2:749864
Subject / course
Information Technology
Presentation
2014-06-04, Grace Hopper, Linköping, 13:38 (Swedish)
Supervisors
Examiners
Available from: 2014-10-09 Created: 2014-09-25 Last updated: 2014-10-09Bibliographically approved

Open Access in DiVA