COMET: Weak-tie hypothesis in complex digital networks
Funders
Academy project funded by the Research Council of Finland (2024-2028)
Leaders
This project, funded by the Research Council of Finland for 2024-28, focuses on studying how innovations spread in social networks. Social network theory predicts that innovations and new ideas spread most effectively through individuals who are loosely connected in networks. Numerous observations from a range of fields support this theory, but their evidence is mainly based on very small networks. This cross-disciplinary project tests the validity of the theory by examining how linguistic innovations spread in extremely large social media networks. The group brings together leading computational humanities experts, sociolinguists and computer scientists.
In addition to advancing basic research, this project leads to considerable societal impact, since the technical tools developed can be used to model the spread of disinformation in social media effectively.
News
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COMET: Research project funded by the Research Council of Finland (2024-2028)COMET: Research project funded by the Research Council of Finland (2024-2028)
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Several COMET researchers at ISLE8Several COMET researchers at ISLE8
Several COMET researchers will present their ongoing work at the 8th Conference of the International Society for the Linguistics of English (ISLE)… -
COMET researchers win Best Paper AwardCOMET researchers win Best Paper Award
Masoud Fatemi, Mikko Laitinen and Pasi Fränti have been awarded the Best Paper prize at ISKE2025 conference in China! See below.
COMET researchers win Best Paper Award
Masoud Fatemi, Mikko Laitinen and Pasi Fränti have been awarded the Best Paper prize at ISKE2025 conference in China! The title of the paper is “Clustering Digital Ego Networks by Tie Strength: A Scalable, Platform-independent Method”.
Abstract:
This study presents a scalable method to classify online social networks based on tie strength. Utilizing ego networks from Twitter, we applied four measurable features—interaction strength, relative interaction strength, social similarity, and outlier ratio—to cluster over 8,000 networks into four categories: weak, moderately-weak, moderately-strong, and strong ties. Our approach is not platform-dependent and overcomes the limitations of previous methods that relied on fixed thresholds or manual labeling. The results reveal regional and gender-based differences in tie strength patterns: Nordic users tend to form weaker ties, while users in Australia, the UK, and the US are more likely to build stronger-tie networks. Male users dominate across all tie categories, while female and uncategorized users are more common in weaker networks. The findings can support research in online social behavior, content delivery, and information diffusion.
Files
1 itemsKeywords
Leaders
Professors
Senior Researchers
Doctoral Researchers
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Irene Taipale
Doctoral ResearcherSchool of Humanities, Philosophical Faculty -
Rahel Albicker
Doctoral ResearcherSchool of Humanities, Philosophical Faculty -
Masoud Fatemi
Doctoral ResearcherSchool of Humanities, Philosophical Faculty -
Mehrdad Salimi
Project ResearcherSchool of Humanities, Philosophical Faculty -
Chunyuan Nie
Project ResearcherSchool of Humanities, Philosophical Faculty
Technicians
Publications
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Detecting Connectivity Patterns in Nordic Twittersphere by Cluster Analysis
Fatemi, Masoud; Sieranoja, Sami; Laitinen, Mikko; Fränti, Pasi, 2025, SN computer science, 6, 7, 815. A1 Journal article (refereed), original research -
Do we swear more with friends or with acquaintances? F#ck in social networks
Laitinen, Mikko; Rautionaho, Paula; Fatemi, Masoud; Halonen, Mikko, 2025, Lingua, 320, 103931. A1 Journal article (refereed), original research -
From tweets to networks: Introducing four large network-based social media corpora
Fatemi, Masoud; Laitinen, Mikko, 2025, CLARIN annual conference proceedings. Abstract -
Reuse of social media data in corpus linguistics
Laitinen, Mikko; Rautionaho, Paula, 2025, International journal of corpus linguistics, 30, 2, 171-194. A1 Journal article (refereed), original research -
Testing the weak-tie hypothesis with social media
Laitinen, Mikko; Fatemi, Masoud, 2024, Poudat, Céline; Guernut, Mathilde, Proceedings of the 11th Conference on computer-mediated communication and social media corpora, 46-51. D3 Professional conference proceedings -
Data-intensive sociolinguistics using social media
Laitinen, Mikko; Fatemi, Masoud, 2023, Annales Academiae Scientiarum Fennicae, 2023, 2, 38-61. A1 Journal article (refereed), original research -
Big and rich social networks in computational sociolinguistics
Laitinen, Mikko; Fatemi, Masoud, 2022, Rautionaho, Paula; Parviainen, Hanna; Kaunisto, Mark; Nurmi, Arja, Social and Regional Variation in World Englishes : Local and Global Perspectives, 166-190. A3 Book section, Chapters in research books -
Towards Visual Sociolinguistic Network Analysis
Kucher, Kostiantyn; Fatemi, Masoud; Laitinen, Mikko, 2021, Hurter, Christophe; Purchase, Helen; Braz, Jose; Bouatouch, Kadi, Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - IVAPP (Volume 3), 248-255. A4 Conference proceedings -
Size matters: Digital social networks and language change
Laitinen, Mikko; Fatemi, Masoud; Lundberg, Jonas, 2020, Frontiers in artificial intelligence and applications, 3, 46. A1 Journal article (refereed), original research -
The Nordic tweet stream: A dynamic real-Time monitor corpus of big and rich language data
Laitinen, Mikko; Lundberg, Jonas; Levin, Magnus; Martins, Rafael, 2018, Tolonen, M; Tuominen, J; Makela, E, 3rd Conference on Digital Humanities in the Nordic Countries, DHN 2018; Helsinki; Finland; 7 March 2018 through 9 March 2018, 349-362. A4 Conference proceedings
