119 research outputs found

    Influence of augmented humans in online interactions during voting events

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    The advent of the digital era provided a fertile ground for the development of virtual societies, complex systems influencing real-world dynamics. Understanding online human behavior and its relevance beyond the digital boundaries is still an open challenge. Here we show that online social interactions during a massive voting event can be used to build an accurate map of real-world political parties and electoral ranks. We provide evidence that information flow and collective attention are often driven by a special class of highly influential users, that we name "augmented humans", who exploit thousands of automated agents, also known as bots, for enhancing their online influence. We show that augmented humans generate deep information cascades, to the same extent of news media and other broadcasters, while they uniformly infiltrate across the full range of identified groups. Digital augmentation represents the cyber-physical counterpart of the human desire to acquire power within social systems.Comment: 11 page

    Evolution of Online User Behavior During a Social Upheaval

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    Social media represent powerful tools of mass communication and information diffusion. They played a pivotal role during recent social uprisings and political mobilizations across the world. Here we present a study of the Gezi Park movement in Turkey through the lens of Twitter. We analyze over 2.3 million tweets produced during the 25 days of protest occurred between May and June 2013. We first characterize the spatio-temporal nature of the conversation about the Gezi Park demonstrations, showing that similarity in trends of discussion mirrors geographic cues. We then describe the characteristics of the users involved in this conversation and what roles they played. We study how roles and individual influence evolved during the period of the upheaval. This analysis reveals that the conversation becomes more democratic as events unfold, with a redistribution of influence over time in the user population. We conclude by observing how the online and offline worlds are tightly intertwined, showing that exogenous events, such as political speeches or police actions, affect social media conversations and trigger changes in individual behavior.Comment: Best Paper Award at ACM Web Science 201

    Contentious Responses to the Crises in Spain : Emphasis Frames and Public Support for Protest on Twitter and the Press.

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    This research analyzes how different types of frames adopted by news organizations and social media affected the support for protests against austerity measures in Spain. We pay special attention to the individual understandings of the crises based on materialistic grievances and nonmaterialistic accounts of the economic crises. We identified frames using a supervised approach and a data set of 2 million tweets gathered during the major demonstrations of the Indignados Movement between 2011 and 2013. Our second data set included the news-related content published by the top Spanish newspapers, in terms of circulation, during those demonstrations. We found that support for antiausterity protests was conditioned by understandings of the crisis. Frames addressing the political system were negatively related to the support for protests against austerity measures, as compared with those referring to the crisis as an economic matter. In addition, more challenging and controversial frames generated lower acceptance of the protests among the population than those that primed social problems

    Characterizing interactions in online social networks during exceptional events

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    Nowadays, millions of people interact on a daily basis on online social media like Facebook and Twitter, where they share and discuss information about a wide variety of topics. In this paper, we focus on a specific online social network, Twitter, and we analyze multiple datasets each one consisting of individuals' online activity before, during and after an exceptional event in terms of volume of the communications registered. We consider important events that occurred in different arenas that range from policy to culture or science. For each dataset, the users' online activities are modeled by a multilayer network in which each layer conveys a different kind of interaction, specifically: retweeting, mentioning and replying. This representation allows us to unveil that these distinct types of interaction produce networks with different statistical properties, in particular concerning the degree distribution and the clustering structure. These results suggests that models of online activity cannot discard the information carried by this multilayer representation of the system, and should account for the different processes generated by the different kinds of interactions. Secondly, our analysis unveils the presence of statistical regularities among the different events, suggesting that the non-trivial topological patterns that we observe may represent universal features of the social dynamics on online social networks during exceptional events

    #weAreMaunaKea: celebrity involvement in a protest movement

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    This study examines the involvement of celebrities in Twitter hashtag networks formed in relation to the protest of the construction of a thirty-meter telescope on Mauna Kea, a volcanic mountaintop that is considered as the most sacred of all peaks in the Hawai'ian islands. A network of 4151 Twitter users who used the hashtag #WeAreMaunaKea is used to examine celebrity involvement. Three network metrics (eigenvector centrality, betweenness centrality, and PageRank) were used to examine the prominence of actors in the network. The results show that three celebrities (Nicole Scherzinger, Kelly Slater, and Keahu Kahuanui) have considerable centrality in the network. The results also indicate a positive correlation between in-degree (prestige), out-degree (engagement), and the three metrics. However, the number of followers did not correlate with the centrality of actors. Nicole Scherzinger, who had higher in-degree and out-degree than the others dominated the network in terms of all three metrics. In general, the results indicated that both prestige and engagement matter in celebrity influence

    The role of hidden influentials in the diffusion of online information cascades

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    In a diversified context with multiple social networking sites, heterogeneous activity patterns and different user-user relations, the concept of "information cascade" is all but univocal. Despite the fact that such information cascades can be defined in different ways, it is important to check whether some of the observed patterns are common to diverse contagion processes that take place on modern social media. Here, we explore one type of information cascades, namely, those that are time-constrained, related to two kinds of socially-rooted topics on Twitter. Specifically, we show that in both cases cascades sizes distribute following a fat tailed distribution and that whether or not a cascade reaches system-wide proportions is mainly given by the presence of so-called hidden influentials. These latter nodes are not the hubs, which on the contrary, often act as firewalls for information spreading. Our results are important for a better understanding of the dynamics of complex contagion and, from a practical side, for the identification of efficient spreaders in viral phenomena.Comment: Submitted to EPJ Data Scienc
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