lnu.sePublications
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • 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
Sentiment analysis in social events
Linnaeus University, Faculty of Social Sciences, Department of Social Studies.
2018 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

Purpose: The purpose of this study is going to visualize the public sentiment on expected and unexpected social events. Exploring the relationship between tweets forwarding and sentiment.

Design/methodology/approach: This research related to sentiment analysis of social events applied a lexicon-based method. The social events come from Facebook data breach and Ireland vote on abortion event. The study conducted This study focused on how the public sentiment changes over time and the relationship between sentiment and tweet forwarding. Bing lexicon and NRC lexicon are adopted in the analysis.

Result: The result of this study is the dominant sentiment trend is consistent with the trend of the number of tweets over time in the Facebook data breach and Ireland vote on abortion. Besides, the sentiment has affected people forward tweets in this research.

Place, publisher, year, edition, pages
2018. , p. 43
Keywords [en]
sentiment, analysis, events, lexicon-based method, forwarding tweets
National Category
Social Sciences
Identifiers
URN: urn:nbn:se:lnu:diva-78077OAI: oai:DiVA.org:lnu-78077DiVA, id: diva2:1252027
Subject / course
Sociologi
Presentation
2018-08-31, K3040, Universitetsplatsen 1, K building, Växjö, 10:15 (English)
Supervisors
Examiners
Available from: 2019-01-03 Created: 2018-09-28 Last updated: 2019-01-03Bibliographically approved

Open Access in DiVA

Final Thesis Revision(1187 kB)4 downloads
File information
File name FULLTEXT01.pdfFile size 1187 kBChecksum SHA-512
592241146f6458e8b5e001c7851f2dc1c909978356603092e6400850216ce3946ba0ac2f14d4443297d5a3953b89a05779c466ba7db094d7f7c8bae2d2feffe1
Type fulltextMimetype application/pdf

Search in DiVA

By author/editor
Liu, Qiaoshan
By organisation
Department of Social Studies
Social Sciences

Search outside of DiVA

GoogleGoogle Scholar
Total: 4 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

urn-nbn

Altmetric score

urn-nbn
Total: 26 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • 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