Network Analysis of Digital and Social Media

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    Analysis of the Twitter Interactions during the Impeachment of Brazilian President
    ( 2018-01-03) de França, Fabrício Olivetti ; Goya, Denise ; Penteado, Claudio Camargo
    The impeachment process that took place in Brazil on April, 2016, generated a large amount of posts on Internet Social Networks. These posts came from ordinary people, journalists, traditional and independent media, politicians and supporters. Interactions among users, by sharing news or opinions, can show the dynamics of communication inter and intra groups. This paper proposes a method for social networks interactions analysis by using motifs, frequent interactions patterns in network. This method is then applied to analyze data extracted from Twitter during the voting for the impeachment of the Brazilian president. Results of this analysis highlight the behavior of some users by retweeting each other to increase the importance of their opinion or to reach visibility. In addition, interaction patterns reveal that messages from one group (against/in favor of impeachment) rarely propagate to the opposing group. As such, this brings evidence that Social Networks may not stimulate a debate, but reaffirm users’ beliefs.
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    Emerging Leaderships in an Online Community: A Longitudinal Network Analysis
    ( 2018-01-03) Lee, Joyce ; Yang, Chin-Sheng ; Hsu, Carol ; Wang, Jhong-Heng
    Online communities have brought great benefits to society; however, relatively few of them are successful in sustaining community activities. It is necessary to have a better understanding of the contextual development of online communities. This study adopts the theory of networked influence to address the research objective. Data is collected from an online community which has been in operation for ten years. We investigate the community’s sustainability on a longitudinal basis, focusing on its dynamic temporal development, with regard to how it was formed, became robust, and either declined or was sustained. Adopting social network analysis with a qualitative approach, we identify several types of emerging leaders and how the "relay events" between them had a significant impact on communication prolongation. Their influence is found to extend across discussion entities, resulting in communication homogeneity, and leading to significant network effects that are relevant to participants’ interactions.
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    Sampling Social Media: Supporting Information Retrieval from Microblog Data Resellers with Text, Network, and Spatial Analysis
    ( 2018-01-03) Buntain, Cody ; McGrath, Erin ; Behlendorf, Brandon
    This paper presents a computationally assisted method for scaling researcher expertise to large, online social media datasets in which access is constrained and costly. Developed collaboratively between social and computer science researchers, this method is designed to be flexible, scalable, cost-effective, and to reduce bias in data collection. Online response to six case studies covering elections and election-related violence in Sub-Saharan African countries are explored using Twitter, a popular online microblogging platform. Results show: 1) automated query expansion can mitigate researcher bias, 2) machine learning models combining textual, social, temporal, and geographic features in social media data perform well in filtering data unrelated to the target event, and 3) these results are achievable while minimizing fee-based queries by bootstrapping with readily-available Twitter samples.
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    Press Freedom Homophily in the Tie Structure of the Global Internet
    ( 2018-01-03) Seo, Hyunjin ; Thorson, Stuart
    We investigate homophily in the tie structure of the global Internet by estimating Exponential Random Graph models. Specifically, we analyze the extent to which different variables including Gross National Income, geographic proximity, political regime type, and press freedom rating account for the pattern of direct country-to-country Internet connections. Results show that for 2011-2014, but not before, press freedom homophily is significantly predictive of the presence (or absence) of country-to-country Internet connections even when controlling for geographic proximity, bandwidth, and whether or not a country is democratic. The findings provide insights into changes in press freedom around the world and the evolution of the global Internet structure.
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