Network Analysis of Digital and Social Media

Permanent URI for this collection


Recent Submissions

Now showing 1 - 5 of 5
  • Item
    Does Our World “weigh” Less Right Now? The Gravitational Pull in a Scientific Collaboration Network is Getting Weaker with Time
    ( 2020-01-07) Kelman, Guy ; Levy, Moshe ; Manes, Eran
    We study the geographical patterns of scientific collaboration from a large sample of research papers and letters written by two authors that appeared in the magazine Nature over two sub-periods, before and after the popularization of Internet use. We report three results: First, the distance distribution of co-authors is fat-tailed, in agreement with other studies that find gravitational law in collaboration networks. Second, in the later period the distance distribution dominates the range of commute-distance and beyond (>50km), which renders the city the atomic unit for statistical testing. Last, strong geographical clustering remains a major generative factor in this network. Assuming the universality of this law, we estimate the gravitational constant from the pull between scientists in the network. We find that this constant has decreased two-fold over the last three decades while the other coefficients remain stable. This may indicate that the gravitational constant absorbs changes in the environment that render distances easier to cross, namely a “lighter world”
  • Item
    Global Contagion of Non-Viral Information
    ( 2020-01-07) Bartal, Alon ; Ravid, Gilad ; Tsur, Oren
    Contagion in Online Social Networks (OSN) is typically measured by the tendency of users to re-post information or to adopt a new behavior after exposure to that information/behavior. Most contagion research is bound by modeling: (i) only local neighbor-to-neighbor contagion (ii) the spread of viral information. However, most contagion events are non-viral and can also occur globally by non-neighbors through for example, exposure to information by exploratory browsing, or by content recommendation algorithms. This study is the first to address the phenomenon of both global and local contagion of non-viral information in a quantitative way. Analysis of Twitter networks reveals the prevailing nature of global contagion, the different temporal patterns between global and local contagion, and the ways it varies across topical categories. An interesting finding shows that users who retweeted due to global contagion have more Followers than those who retweeted due to local contagion.
  • Item
    Bucking the Trend: An Agentive Perspective of Managerial Influence on Blog’S Attractiveness
    ( 2020-01-07) Santos, Carlos ; Castro, I ; Onoyama, Silvia ; Moreira, Marina
    Blog management is central to the digitalization of work. However, existing theories tend to focus on environmental influence rather than managerial control of a blog’s attractiveness at a microlevel. This study provides an agentive account of the adaptive behaviours exerted by the bloggers through the ways they use contents of their blogs to locate and harness their structural network positions of a blogosphere. We collated individual characteristics of 165 bloggers who blogged about economics, and then analysed the ways they maintained the contents of their blogs. We used network analysis and monomial logistic regression to test our model predictions. Our findings show that in contrast to less attractive blogs, bloggers who are mindful of their peers’ contents as a means of maintaining network positions attract a significantly higher level of traffic to their blogs. This agentive perspective offers practical insights into how nodal preferences can be reversed in blog management. We conclude the paper by discussing contributions to theory and future research.
  • Item
    The Effect of Turnover Intention on Tie Formation in Online Organization Networks
    ( 2020-01-07) Chipidza, Wallace ; Tripp, John
    Turnover is costly for organizations. While existing research identifies the antecedents and effects of turnover, little research exists on how to identify individuals intending to leave an organization. We hypothesize that individuals with high turnover intention will participate in fewer communication relationships than average, and that individuals prefer communicating with others of similar levels of turnover intention. We use exponential random graph modeling (ERGM) to test our hypotheses on the email and advice networks of a technology company. ERGM allows us to simultaneously examine the effect of individual and dyadic level attributes on network formation. The results support our hypotheses in the email network, but not in the advice network. Our findings imply that organizations should examine their email networks to identify individuals with high turnover intention, and intervene with incentives if they wish to retain the employees.
  • Item
    Introduction to the Minitrack on Network Analysis of Digital and Social Media
    ( 2020-01-07) Chu, Kar-Hai ; Rosen, Devan ; Barnett, George