2016- Working Papers: Technology and Information Systems

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Using retweets to shape our online persona:  A topic modeling approach, 53 pp. 
H. Geva, G. Oestreicher-Singer and M. Saar-Tsechansky
(Working Paper no. 4/2016)
Research no.: 05060100

Online social networking technologies have given rise to new social behaviors, with the like on Facebook being a prominent example. We study a specific type of social behavior: the ability to reiterate a friend’s activity, that is, to redistribute an exact copy of content that he or she has posted online (e.g., words, videos, or pictures). Such reiteration tools enable the user to leverage someone else’s self-expression to enhance his or her own image as reflected by the online platform. We focus on the effects of such reiteration tools on the way users present themselves online. Specifically, using data from Twitter we ask: (1) Do users utilize retweets to expand the breadth of topics they discuss, by adding topics not discussed in their self-tweets, or do they use it to enhance their self-produced persona, adding further content relating to the topics they already discuss in their self-tweets? (2) Do users utilize the retweet option to change the distribution of the topics they discuss in their self-tweets? (3) Do those behaviors differ between expert users and non-expert users? We analyzed data taken from Twitter over a period of 3 weeks in 2015, with regard to 2,435 non-expert core users (defined as users who tweet regularly and are likely to use the platform for personal rather than professional purposes), 415 expert users and the users whom they followed. We use LDA topic modeling to derive the topics in both self-tweets and re-tweets of each user. We find that users rarely add new topics to their profile when retweeting; instead, they enrich their persona by deepening the discussion of topics that they address in their self-tweets. Furthermore, we find that a user's retweets do remarkably little to alter the distribution of topics she discusses in her self-tweets. Finally, we find that both non-expert and expert users tend to add few new topics via retweets, and that this tendency is stronger among expert users. Specifically, on average, experts retweet less often and add fewer topics per tweet, indicating that they rely more on their own words when engaging in impression management.

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Community impact on crowdfunding performance, 43 pp. 
Y. Inbar and O. Barzilay
(Working Paper no. 13/2016)
Research no.: 02850100

Many digital platforms, regardless of their business domain, follow the common practice of incorporating social and community features in order to increase their user engagement and expand their online community. Although this practice is advocated by the literature and clearly makes sense, its implications are not well understood. In this research, we aimed to close this literature gap, providing a theoretical framework and empirical evidence regarding the impact of the online community on platform performance. As a testbed, we studied crowdfunding platforms, that is, designated websites aimed at enabling entrepreneurs to raise money over the Internet. We used comprehensive data collected from Kickstarter, the largest crowdfunding platform established to date. We theorized that online platforms, such as Kickstarter, consist not of a single community but rather a hierarchy of multiple, partially competing communities. These communities vary considerably with respect to the interests of their members, their platform participation patterns, and their impact on platform performance. Our suggested framework incorporates the notion of fluidity of online communities; that is, online users and digital communities evolve and change over time. As the interests of the online user change, so does the membership of her immediate community. The proposed framework allows us to identify such community changes and, consequently, to better identify pivotal members of online communities and predict their lifetime value as potential backers. Empirically, we validated our theory by studying the participation patterns of over 6.3 million Kickstarter users, who have supported more than 150 thousand crowdfunding campaigns over more than 5 years. We demonstrated the growth of the different community types and estimated their different impacts on crowdfunding performance over time. Interestingly, we found that some communities, despite high participation rates, had negative impacts on crowdfunding campaign success. We discuss managerial and practical implications of our theory and findings.

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