Distinguishing Topical and Social Groups Based on Common Identity and Bond Theory

Social groups play a crucial role in social media platforms because they form the basis for user participation and engagement. Groups are created explicitly by members of the community, but also form organically as members interact. Due to their importance, they have been studied widely (e.g., community detection, evolution, activity, etc.). One of the key questions for understanding how such groups evolve is whether there are different types of groups and how they differ. In Sociology, theories have been proposed to help explain how such groups form. In particular, the common identity and common bond theory states that people join groups based on identity (i.e., interest in the topics discussed) or bond attachment (i.e., social relationships). The theory has been applied qualitatively to small groups to classify them as either topical or social. We use the identity and bond theory to define a set of features to classify groups into those two categories. Using a dataset from Flickr, we extract user-defined groups and automatically-detected groups, obtained from a community detection algorithm. We discuss the process of manual labeling of groups into social or topical and present results of predicting the group label based on the defined features. We directly validate the predictions of the theory showing that the metrics are able to forecast the group type with high accuracy. In addition, we present a comparison between declared and detected groups along topicality and sociality dimensions.Comment: 10 pages, 6 figures, 2 table

Link creation and profile alignment in the aNobii social network

The present work investigates the structural and dynamical properties of aNobii\footnote{http://www.anobii.com/}, a social bookmarking system designed for readers and book lovers. Users of aNobii provide information about their library, reading interests and geographical location, and they can establish typed social links to other users. Here, we perform an in-depth analysis of the system's social network and its interplay with users' profiles. We describe the relation of geographic and interest-based factors to social linking. Furthermore, we perform a longitudinal analysis to investigate the interplay of profile similarity and link creation in the social network, with a focus on triangle closure. We report a reciprocal causal connection: profile similarity of users drives the subsequent closure in the social network and, reciprocally, closure in the social network induces subsequent profile alignment. Access to the dynamics of the social network also allows us to measure quantitative indicators of preferential linking.Comment: http://www.iisocialcom.org/conference/socialcom2010

Online Popularity and Topical Interests through the Lens of Instagram

Online socio-technical systems can be studied as proxy of the real world to investigate human behavior and social interactions at scale. Here we focus on Instagram, a media-sharing online platform whose popularity has been rising up to gathering hundred millions users. Instagram exhibits a mixture of features including social structure, social tagging and media sharing. The network of social interactions among users models various dynamics including follower/followee relations and users' communication by means of posts/comments. Users can upload and tag media such as photos and pictures, and they can "like" and comment each piece of information on the platform. In this work we investigate three major aspects on our Instagram dataset: (i) the structural characteristics of its network of heterogeneous interactions, to unveil the emergence of self organization and topically-induced community structure; (ii) the dynamics of content production and consumption, to understand how global trends and popular users emerge; (iii) the behavior of users labeling media with tags, to determine how they devote their attention and to explore the variety of their topical interests. Our analysis provides clues to understand human behavior dynamics on socio-technical systems, specifically users and content popularity, the mechanisms of users' interactions in online environments and how collective trends emerge from individuals' topical interests.Comment: 11 pages, 11 figures, Proceedings of ACM Hypertext 201

Linking geosocial sensing with the socio-demographic fabric of smart cities

Technological advances have enabled new sources of geoinformation, such as geosocial media, and have supported the propagation of the concept of smart cities. This paper argues that a city cannot be smart without citizens in the loop, and that a geosocial sensor might be one component to achieve that. First, we need to better understand which facets of urban life could be detected by a geosocial sensor, and how to calibrate it. This requires replicable studies that foster longitudinal and comparative research. Consequently, this paper examines the relationship between geosocial media content and socio-demographic census data for a global city, London, at two administrative levels. It aims for a transparent study design to encourage replication, using Term Frequency—Inverse Document Frequency of keywords, rule-based and word-embedding sentiment analysis, and local cluster analysis. The findings of limited links between geosocial media content and socio-demographic characteristics support earlier critiques on the utility of geosocial media for smart city planning purposes. The paper concludes that passive listening to publicly available geosocial media, in contrast to pro-active engagement with citizens, seems of limited use to understand and improve urban quality of life

Dynamics in online social networks

An increasing number of today's social interactions occurs using online social media as communication channels. Some online social networks have become extremely popular in the last decade. They differ among themselves in the character of the service they provide to online users. For instance, Facebook can be seen mainly as a platform for keeping in touch with close friends and relatives, Twitter is used to propagate and receive news, LinkedIn facilitates the maintenance of professional contacts, Flickr gathers amateurs and professionals of photography, etc. Albeit different, all these online platforms share an ingredient that pervades all their applications. There exists an underlying social network that allows their users to keep in touch with each other and helps to engage them in common activities or interactions leading to a better fulfillment of the service's purposes. This is the reason why these platforms share a good number of functionalities, e.g., personal communication channels, broadcasted status updates, easy one-step information sharing, news feeds exposing broadcasted content, etc. As a result, online social networks are an interesting field to study an online social behavior that seems to be generic among the different online services. Since at the bottom of these services lays a network of declared relations and the basic interactions in these platforms tend to be pairwise, a natural methodology for studying these systems is provided by network science. In this chapter we describe some of the results of research studies on the structure, dynamics and social activity in online social networks. We present them in the interdisciplinary context of network science, sociological studies and computer science.Comment: 17 pages, 4 figures, book chapte

WRI's Governance Strategy, 2016-2020

Transparent, effective, accountable governance is critical to ensuring that development benefits people and the planet. The Governance Center of Excellence works with civil society, governments, development agencies, businesses, and other institutions to improve decision-making processes and legal frameworks. Our goal is to empower people and strengthen institutions to foster environmentally sound and socially equitable decision-making.In many countries, citizens and communities face social and environmental injustices that can leave them without a say in the development decisions that affect their lives and the resources they depend on.As a global leader on environmental governance, the Governance Center uses data and research to institutionalize fundamental democratic principles - such as transparency, participation, and accountability - into decision-making processes, policies, and legal frameworks. The Governance Center is divided into five practice areas—climate resilience, environmental democracy, energy governance, natural resource governance and urban governance— where our work is concentrated on six priority issues: climate, energy, food, forests, water, and cities

Evolution of the Field of Social Media Research through Science Maps (2008-2017)

The objectives of this work were to discover the main points of interest in the field of research on Social Media, within the scientific area of Communication, and to analyse how it has evolved. A methodology based on the analysis of co-words and visualisation techniques was applied. The data was obtained from scientific publications indexed in the Web of Science (WoS) database, during the periods 2008-2012 and 2013-2017. The resulting maps showed that, during the period 2008-2012, the main areas of interest were web 2.0 and the internet in terms of social networking sites. However, during the period 2013-2017, there was a strong upward trend in the impact of social networks and platforms, especially Twitter and Facebook, in many areas (such as social movements, public relations and publicity, distribution of content, crisis communication, participatory journalism, political communication, or the configuration of public identities through social platforms, with special emphasis on youth). Finally, new scientific challenges were found in automatic analysis of content and management of big data. In conclusion, it was possible to transform a complex, underlying, dynamic and multidimensional reality into visible representations that could help experts in the field to better understand the evolution of research on Social Media

Using Cloudworks to Support OER Activities

This report forms the third and final output of the Pearls in the Clouds project, funded by the Higher Education Academy. It focuses on evaluation of the use of a social networking site, Cloudworks, to support evidence-based practice. The aim of this project (Pearls in the Clouds) has been to evaluate the ways in which web 2.0 tools like Cloudworks can support evidence-informed practices in relation to learning and teaching. We have reviewed evidence from empirically grounded studies surrounding the uses of web2.0 in higher education and highlighted the gap between using web2.0 to support learning and teaching, and using it to support learning about learning and teaching (in an evidence-informed way) (Conole and Alevizou, 2010). We have reported on findings from a case study focusing on the use of Cloudworks by a community of practice - educational technologists - reflecting upon, and, negotiating their role in enhancing teaching and learning in higher education (Galley et al., 2010). The object of this study is to explore and evaluate the use of the site by individuals and communities involved in the production of, and research on, the development, delivery and use of Open Educational Resources (OER)