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It takes two to tango: Exploring social tie development with both online and offline interactions
Author(s) -
Yin Peifeng,
He Qi,
Liu Xingjie,
Lee WangChien
Publication year - 2016
Publication title -
statistical analysis and data mining: the asa data science journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.381
H-Index - 33
eISSN - 1932-1872
pISSN - 1932-1864
DOI - 10.1002/sam.11265
Subject(s) - online and offline , computer science , interpersonal ties , social relation , key (lock) , social network (sociolinguistics) , online participation , heuristic , data science , social media , internet privacy , world wide web , artificial intelligence , psychology , the internet , social psychology , computer security , operating system
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.