Popularity Evolution of Professional Users on Facebook

Popularity in social media is an important objective for professional users (e.g. companies, celebrities, and public figures, etc). A simple yet prominent metric utilized to measure the popularity of a user is the number of fans or followers she succeed to attract to her page. Popularity is influenced by several factors which identifying them is an interesting research topic. This paper aims to understand this phenomenon in social media by exploring the popularity evolution for professional users in Facebook. To this end, we implemented a crawler and monitor the popularity evolution trend of 8k most popular professional users on Facebook over a period of 14 months. The collected dataset includes around 20 million popularity values and 43 million posts. We characterized different popularity evolution patterns by clustering the users temporal number of fans and study them from various perspectives including their categories and level of activities. Our observations show that being active and famous correlate positively with the popularity trend

Evolution of Ego-networks in Social Media with Link Recommendations

Ego-networks are fundamental structures in social graphs, yet the process of their evolution is still widely unexplored. In an online context, a key question is how link recommender systems may skew the growth of these networks, possibly restraining diversity. To shed light on this matter, we analyze the complete temporal evolution of 170M ego-networks extracted from Flickr and Tumblr, comparing links that are created spontaneously with those that have been algorithmically recommended. We find that the evolution of ego-networks is bursty, community-driven, and characterized by subsequent phases of explosive diameter increase, slight shrinking, and stabilization. Recommendations favor popular and well-connected nodes, limiting the diameter expansion. With a matching experiment aimed at detecting causal relationships from observational data, we find that the bias introduced by the recommendations fosters global diversity in the process of neighbor selection. Last, with two link prediction experiments, we show how insights from our analysis can be used to improve the effectiveness of social recommender systems.Comment: Proceedings of the 10th ACM International Conference on Web Search and Data Mining (WSDM 2017), Cambridge, UK. 10 pages, 16 figures, 1 tabl

An empirical analysis of SNS users and their privacy and security awareness of risks associated with sharing SNS profiles (online identities)

Social networking sites (SNS) like MySpace, Facebook and LinkedIn now have hundreds of millions of users. In this paper a quantitative approach was used to analyse primary data collected about SNS users. Our findings show that SNS users are dominated by younger adults, higher education levels and higher income levels. SNSs are more likely to be used for maintaining existing friendships as opposed to establishing new friendships and for building business networks. SNS users either have poor levels of privacy and security awareness or high levels of complacency in relation to SNS profile sharing and sharing their identity online

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

New Media, Professional Sport and Political Economy

New media technologies are seen to be changing the production, delivery and consumption of professional sports and creating a new dynamic between sports fans, athletes, clubs, governing bodies and the mainstream media. However, as Bellamy and McChesney (2011) have pointed out, advances in digital technologies are taking place within social, political, and economic contexts that are strongly conditioning the course and shape of this communication revolution. This essay assesses the first wave of research on professional sport and new media technologies and concludes that early trends indicate the continuation of existing neoliberal capitalist tendencies within professional sport. Using the concept of political economy, the essay explores issues of ownership, structure, production and delivery of sport. Discussion focuses on the opportunities sports fans now have available to them and how sports organization and media corporations shifted from an initial position of uncertainty, that bordered on hostility, to one which has seen them embrace new media technologies as powerful marketing tools. The essay concludes by stating as fundamental the issues of ownership and control and advocates that greater cognizance be accorded to underlying economic structures and the enduring, all-pervasive power of neoliberal capitalism and its impact in professional sport

Illuminating an Ecosystem of Partisan Websites

This paper aims to shed light on alternative news media ecosystems that are believed to have influenced opinions and beliefs by false and/or biased news reporting during the 2016 US Presidential Elections. We examine a large, professionally curated list of 668 hyper-partisan websites and their corresponding Facebook pages, and identify key characteristics that mediate the traffic flow within this ecosystem. We uncover a pattern of new websites being established in the run up to the elections, and abandoned after. Such websites form an ecosystem, creating links from one website to another, and by `liking' each others' Facebook pages. These practices are highly effective in directing user traffic internally within the ecosystem in a highly partisan manner, with right-leaning sites linking to and liking other right-leaning sites and similarly left-leaning sites linking to other sites on the left, thus forming a filter bubble amongst news producers similar to the filter bubble which has been widely observed among consumers of partisan news. Whereas there is activity along both left- and right-leaning sites, right-leaning sites are more evolved, accounting for a disproportionate number of abandoned websites and partisan internal links. We also examine demographic characteristics of consumers of hyper-partisan news and find that some of the more populous demographic groups in the US tend to be consumers of more right-leaning sites.Comment: Published at The Web Conference 2018 (WWW 2018). Please cite the WWW versio

Photo filter apps: understanding analogue nostalgia in the new media ecology

As digital media have become more pervasive and entrenched in our daily routines, a nostalgic countertrend has increasingly valued the physical and tactile nature of the analogue image. In the past few years, technologically obsolete devices, such as lo-fi cameras and vinyl records, have not faded out of sight completely but are instead experiencing a comeback. At the same time, digital media capitalise on the nostalgia for the analogue and fetishise the retro aesthetics of old technologies. This article explores the emergence of photo filter and effect applications which allow users to modify digital photos, adding signifiers of age such as washed-out colours, scratches and torn borders. It is argued that these new technologies, with programs such as Instagram, Hipstamatic and Camera 360, bring back the illusory physicality of picture-taking through digital skeuomorphism. Drawing on media archaeology practice, this article interrogates the limits of the retro sensibility and the fetishisation of the past in the context of digital media, in particular by focusing on the case study of the start-up Instagram. This photo filter application neither merely stresses the twilight nature of photography nor represents the straightforward digital evolution of previous analogue features. Rather, it responds to the necessity to feel connected to the past by clear and valued signs of age, mimicking a perceived sense of loss. Faced with the persistent hipster culture and the newness of digital media, photo filter apps create comfortable memories, ageing pictures and adding personal value. As such, it will be argued that this phenomenon of nostalgia for analogue photography can be linked to the concepts of ritual and totem. By providing a critical history of Instagram as a photo-sharing social network, this article aims to explain new directions in the rapidly changing system of connective media