Predicting Tie Strength With Social MediaEric Gilbert and Karrie KarahaliosUniversity of Illinois at Urbana-Champaign[egilber2, kkarahal]@cs.uiuc.eduABSTRACTSocial media treats all users the same: trusted friend or total stranger, with little or nothing in between. In reality, rela-tionships fall everywhere along this spectrum, a topic social science has investigated for decades under the theme of tie strength. Our work bridges this gap between theory and practice. In this paper, we present a predictive model that maps social media data to tie strength. The model builds on a dataset of over 2,000 social media ties and performs quite well, distinguishing between strong and weak ties with over 85% accuracy. We complement these quantitative findings with interviews that unpack the relationships we could not predict. The paper concludes by illustrating how modeling tie strength can improve social media design elements, in-cluding privacy controls, message routing, friend introduc-tions and information prioritization.Author KeywordsSocial media, social networks, relationship modeling, ties, sns, tie strengthACM Classification KeywordsH5.3. Group and Organization Interfaces; Asynchronous interaction; Web-based interaction. INTRODUCTIONRelationships make social media social. Yet, different rela-tionships play different roles. Consider the recent practice of substituting social media friends for traditional job refer-ences. As one hiring manager remarked, by using social media “you’ve opened up your rolodex for the whole world to see” [38]. To the dismay of applicants, employers some-times cold call social media friends expecting a job refer-ence “only to find that you were just drinking buddies.” Although clearly not the norm, the story illustrates a basic fact: not all relationships are created equal.For decades, social science has made much the same case, documenting how different types of relationships impact individuals and organizations [16]. In this line of research, relationships are measured in the currency of tie strength [17]. Loose acquaintances, known as weak ties, can help a friend generate creative ideas [4] or find a job [18]. They also expedite the transfer of knowledge across workgroups [20]. Trusted friends and family, called strong ties, can af-fect emotional health [36] and often join together to lead organizations through times of crisis [24]. Despite many compelling findings along this line of research, social me-dia does not incorporate tie strength or its lessons. Instead, all users are the same: friend or stranger, with little or noth-ing in between. Most empirical work examining large-scale social phenomena follows suit. A link between actors either exists or not, with the relationship having few properties of its own [1, 2, 27].This paper aims to bridge the gap, merging the theory be-hind tie strength with the data behind social media. We ad-dress one central question. With theory as a guide, can so-cial media data predict tie strength? This is more than a methodological or theoretical point; a model of tie strength has the potential to significantly impact social media users. Consider automatically allowing the friends of strong ties to access your profile. Or, as one participant cleverly sug-gested, remaking Facebook’s Newsfeed to get rid of “peo-ple from high school I don't give a crap about.” The model we present builds on a dataset of over 2,000 Facebook friendships, each assessed for tie strength and described by more than 70 numeric indicators. It performs with surpris-ing accuracy, modeling tie strength to 10-point resolution and correctly classifying friends as strong or weak ties more than 85% of the time.We begin by reviewing the principles behind tie strength, and then discuss its proposed dimensions. Using theory to guide the selection of predictive variables, we next present the construction of our tie strength model. It performs well, but not perfectly. To understand our model’s limitations, we also present the results of follow-up interviews about the friendships we had the most difficulty predicting. The paper concludes by applying our findings toward implications for theory and practice.TIE STRENGTHMark Granovetter introduced the concept of tie strength in his landmark 1973 paper “The Strength of Weak Ties” [17]. In this section we review tie strength and the substantial line of research into its characteristics. We then discuss four researchers’ proposals for the dimensions of tie strength, laying a foundation for our treatment of it as a predictable quantity. The section concludes by introducing the research questions that guide the rest of this paper.Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee.CHI 2009, April 4–9, 2009, Boston, Massachusetts, USA.Copyright 2009 ACM 978-1-60558-246-7/09/04...$5.00.CHI 2009 ~ Online RelationshipsApril 6th, 2009 ~ Boston, MA, USA211Definition and ImpactThe strength of a tie is a (probably linear) combination of the amount of time, the emotional intensity, the intimacy (mutual confiding), and the reciprocal services which characterize the tie. [17] While Granovetter left the precise definition of tie strength to future work, he did characterize two types of ties, strong and weak. Strong ties are the people you really trust, people whose social circles tightly overlap with your own. Often, they are also the people most like you. The young, the highly educated and the metropolitan tend to have diverse networks of strong ties [31]. Weak ties, conversely, are merely acquaintances. Weak ties often provide access to novel information, information not circulating in the closely knit network of strong ties.Many researchers have adopted tie strength as an analytic framework for studying individuals and organizations