It takes two to tango: Exploring social tie development with both online and offline interactions

Peifeng Yin, Qi He, Xingjie Liu, Wang Chien Lee

Research output: Contribution to journalArticlepeer-review

5 Scopus citations


Understanding social tie development among users is crucial for user engagement in social networking services. In this paper, we analyze the social interactions, both online and offline, of users and investigate the development of their social ties using data trail of 'how social ties grow' left in mobile and social networking services. To the best of our knowledge, this is the first research attempt on studying social tie development by considering both online and offline interactions in a heterogeneous yet realistic relationship. In this study, we aim to answer three key questions: (i) is there a correlation between online and offline interactions? (ii) how is the social tie developed via heterogeneous interaction channels? and (iii) would the development of social tie between two users be affected by their common friends? To achieve our goal, we develop a Social-aware Hidden Markov Model (SaHMM) that explicitly takes into account the factor of common friends in measure of the social tie development. Our experiments show that, comparing with results obtained using HMM and other heuristic methods, the social tie development captured by our SaHMM is significantly more consistent to lifetime profiles of users.

Original languageEnglish (US)
Pages (from-to)174-187
Number of pages14
JournalStatistical Analysis and Data Mining
Issue number3
StatePublished - Jun 1 2016

All Science Journal Classification (ASJC) codes

  • Analysis
  • Information Systems
  • Computer Science Applications


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