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Troll hunting in the information age
Umeå University, Faculty of Science and Technology, Department of Computing Science.
2015 (Swedish)Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
Abstract [en]

This thesis presents an attempt to use linear regression to predict the number of authors who contributed to a text, in this case a forum. To do this a set of features which is usually used in authorship attribution has been applied. After a functionality for feature extraction was implemented a model was trained on how the number of authors affects the richness of a text. This model is then used to predict how many people contributed to a there-to unseen text. The result of this work shows that it works rather well to guess the number of authors who contributed to a text if the number of authors are fairly small, but as the number of authors grow, it gets harder to guess the number of authors. Possibly because the variance does not grow enough linear for large number of authoers.

Place, publisher, year, edition, pages
2015. , 29 p.
Series
UMNAD, 1027
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:umu:diva-108375OAI: oai:DiVA.org:umu-108375DiVA: diva2:852731
Educational program
Bachelor of Science Programme in Computing Science
Supervisors
Examiners
Available from: 2015-09-10 Created: 2015-09-10 Last updated: 2015-09-10Bibliographically approved

Open Access in DiVA

fulltext(269 kB)140 downloads
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File name FULLTEXT01.pdfFile size 269 kBChecksum SHA-512
35153912c4be1c2ae3f1ae724d49fbbca21de6130a3daddf4d8c544225e8d9150be95409a637be5d4f785628d0b56b533935d96ea97656ae33edd48dd8863046
Type fulltextMimetype application/pdf

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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