The Role of Followers and Followees in the Adoption of Innovations

An online social network is a key platform through which innovation diffuses. To learn about innovativeness, we simultaneously investigate two Twitter networks, the relationships network, following-follower relationships, and the activity network, the flow of tweets. Specifically, the innovativeness relations to the networks' indegree and outdegree, the volume of platform use, and the profile's age. The more active and central the user, the earlier the adoption. Innovativeness increases with the number of followers only when at least several of them adopt the innovation. Surprisingly, having more followees is linked to later engagement with the innovation. This association is mediated by the number of adopters' followees. Those who created a Twitter profile later are also more likely to adopt innovations later. This study is novel in distinguishing between the two networks and analyzing their interactions. Its contribution lies in identifying the innovativeness of users in an online social network platform diffusion

Tracing Community Genealogy: How New Communities Emerge from the Old

The process by which new communities emerge is a central research issue in the social sciences. While a growing body of research analyzes the formation of a single community by examining social networks between individuals, we introduce a novel community-centered perspective. We highlight the fact that the context in which a new community emerges contains numerous existing communities. We reveal the emerging process of communities by tracing their early members' previous community memberships. Our testbed is Reddit, a website that consists of tens of thousands of user-created communities. We analyze a dataset that spans over a decade and includes the posting history of users on Reddit from its inception to April 2017. We first propose a computational framework for building genealogy graphs between communities. We present the first large-scale characterization of such genealogy graphs. Surprisingly, basic graph properties, such as the number of parents and max parent weight, converge quickly despite the fact that the number of communities increases rapidly over time. Furthermore, we investigate the connection between a community's origin and its future growth. Our results show that strong parent connections are associated with future community growth, confirming the importance of existing community structures in which a new community emerges. Finally, we turn to the individual level and examine the characteristics of early members. We find that a diverse portfolio across existing communities is the most important predictor for becoming an early member in a new community.Comment: 10 pages, 7 figures, to appear in Proceedings of ICWSM 2018, data and more at https://chenhaot.com/papers/community-genealogy.htm

Percepções sobre corrupção durante as eleições presidenciais no Brasil em 2018 : uma análise baseada no Twitter

Trabalho de Conclusão de Curso (graduação)—Universidade de Brasília, Faculdade UnB Gama, Engenharia de Software, 2018.Compreender a corrupção e suas nuances, e como elas afetam o cidadão, pode ser um bom caminho para o combate eficaz e eficiente da corrupção. Neste contexto, as redes sociais são uma fonte valiosa para analisar a percepção de um grupo de pessoas. Utilizando tweets do primeiro turno eleitoral do ano de 2018, colhidos por meio da API da plataforma Twitter, esse trabalho apresenta uma análise dos comentários publicados relacionados a corrupção. Para análise dessas falas, foi utilizada a ferramenta IRaMuTeQ, obtendo-se assim análises estatísticas, análises de similitude, classificação hierárquica descendente, nuvem de palavras, entre outros resultados. Ao fim das análises foi possível observar diferentes percepções sobre à corrupção no conjunto de dados referentes a 3395 tweets. Como conclusão, notou-se duas grandes percepções: um grupo que apontava de maneira extremada e radical a corrupção do governo passado, e outro grupo com comentários anticorrupção mais moderados e que criticavam os dois lados do espectro político.Understanding corruption and its nuances, and how they affect the citizen, can be a good way to an effective and efficient combat of corruption. In this context, social networks are a valuable source for analyzing the perception of a group of peoople. Using tweets from the first electoral turn of the year 2018, collected through Twitter’s API platform, this study presents an analysis of the published comments related to corruption. For the analysis of these speeches, the IRaMuTeQ tool was used, obtaining statistical analyzes, similarity analyzes, descending hierarchical classification, word cloud among other results. At the end of the analyzes it was possible to observe different perceptions about corruption in the dataset referring to the 3395 tweets. As conclusion, two great insights were noted: a group that pointed out the corruption of the past government in an extreme and radical way. and another group with more moderate anti-corruption comments that criticized both side of the political spectrum