Change search
ReferencesLink to record
Permanent link

Direct link
Incredible tweets: Automated credibility analysis in Twitter feeds using an alternating decision tree algorithm
KTH, School of Computer Science and Communication (CSC).
2016 (English)Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
Abstract [en]

This project investigates how to determine the credibility of a tweet without using human perception. Information about the user and the tweet is studied in search for correlations between their properties and the credibility of the tweet. An alternating decision tree is created to automatically determine the credibility of tweets.

Some features are found to correlate to the credibility of the tweets, amongst which the number of previous tweets by a user and the use of uppercase characters are the most prominent.

Place, publisher, year, edition, pages
National Category
Computer Science
URN: urn:nbn:se:kth:diva-186711OAI: diva2:927807
Available from: 2016-05-18 Created: 2016-05-13 Last updated: 2016-05-18Bibliographically approved

Open Access in DiVA

fulltext(836 kB)14 downloads
File information
File name FULLTEXT01.pdfFile size 836 kBChecksum SHA-512
Type fulltextMimetype application/pdf

By organisation
School of Computer Science and Communication (CSC)
Computer Science

Search outside of DiVA

GoogleGoogle Scholar
Total: 14 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

Total: 15 hits
ReferencesLink to record
Permanent link

Direct link