Self-Similarity of Twitter Users

被引：0

作者：

Fatemi, Masoud ^{[1
,2
]}

Kucher, Kostiantyn ^{[1
,3
]}

Laitinen, Mikko ^{[1
,2
]}

Franti, Pasi ^{[2
]}

机构：

[1] Linnaeus Univ, Vaxjo Kalmar, Sweden

[2] Univ Eastern Finland, Kuopio, Finland

[3] Linkoping Univ, Norrkoping, Sweden

来源：

PROCEEDINGS OF THE 2021 SWEDISH WORKSHOP ON DATA SCIENCE (SWEDS) | 2021年

关键词：

Social network analysis; Ego network; User similarity; Users interactions; Activity history; SOCIAL NETWORKS;

D O I：

10.1109/SweDS53855.2021.9638288

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Earlier studies have established that the (perceived) similarity of users is highly subjective and reflects more on how people respect/admire others rather than their characteristics or behavioral similarities. We study this phenomenon among Twitter users, and while confirm that it is indeed the case, we further explore the components of similarity by investigating it using data from three categories (interactions between egos and alters, profile-based activity history, and linguistic content in the messages). We use interactions as estimation for admiration and observe that it has more impact and a higher correlation to the perceived similarity than other objective measures, including similarity based on user profiles and their use of hashtags.

引用

页数：7

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