Summary: A comparative study of the communities identified in tweets collected during 2015 and 2016 - how stable communities are, which communities are born or disappear, and how people move between them. A searchable web app was also created making the data available under Creative Commons Zero.
Huss, M, Östmar, M Dynamics in Swedish Twitter communities 2017-02-27
Summary: An attempt to use word vectors to analyse culture. The author has analysed word2vec word embeddings trained on English and Swedish wikipedia corpuses, to examine whether there are particular areas of expression that are enriched or depleted in one language compared to another.
Whitington, T Using word vectors to decipher Swedish culture 2017-01-01
Summary: We identify communities in the Swedish twitterverse by analyzing a large network of millions of reciprocal mentions in a sample of 312,292,997 tweets from 435,792 twitter accounts in 2015 and show that politically meaningful communities among others can be detected without having to read or search for specific words or phrases.
Östmar, M, Huss, M The big picture of public discourse on Twitter by clustering metadata 2016-12-29
Summary: We looked through 2,010,781 tweets for expressions of gratitude by using any form of the word "tack" (thanks), aggregated that by user and calculated a weighted gratitutde-score. Thereby we where able to present a top list of the most grateful Twitter accounts.
Östmar, M Tacksammast på Twitter - hela listan. 2016-03-10
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