Communication Technology and New Media Commons^™

Social Media For Good? A Survey On Millennials’ Inspirational Social Media Use, Sophie Janicke-Bowles, Ava Nayaran, Anja Seng

Communication Faculty Articles and Research

There is no doubt about the extensive use of social media by the millennial generation, but the study of the effects of such use is only in its infancy. Though most studies so far focus on the negative effects of overall time spent on social media, the current study investigated the relationship between exposure to a specific type of content on social media and well-being outcomes: namely, inspirational content. Results of an online survey with a total of 146 students revealed that inspiring social media and online video use, but not overall time spent on social media was related to …

Professional And Personal Social Networking And Enhancement Of Social Capital In Young Adults, Maria Malu H. Roldan, Janejira Sutanonpaiboon, Richard Burkhard

Journal of International Technology and Information Management

PROFESSIONAL AND PERSONAL SOCIAL NETWORKING AND ENHANCEMENT OF SOCIAL CAPITAL IN YOUNG ADULTS

ABSTRACT

This study compares the use of personal and professional social networking sites by young adults for social capital enhancing activities. The research is based on a survey of college-age adults (n=292) who were asked about their use of two social networking sites of contrasting architectures: the more interactive, social/personal\-oriented site Facebook, and the relatively less interactive, professional/business-oriented site LinkedIn. Data were analyzed to determine the relationships among demographic and technology experience factors, and respondents’ use of these sites for social capital enhancing activities. Findings suggest that …

Tie Strength, Embeddedness, And Social Influence: A Large-Scale Networked Experiment, Sinan Aral, Dylan Walker

Business Faculty Articles and Research

We leverage the newly emerging business analytical capability to rapidly deploy and iterate large-scale, microlevel, in vivo randomized experiments to understand how social influence in networks impacts consumer demand. Understanding peer influence is critical to estimating product demand and diffusion, creating effective viral marketing, and designing “network interventions” to promote positive social change. But several statistical challenges make it difficult to econometrically identify peer influence in networks. Though some recent studies use experiments to identify influence, they have not investigated the social or structural conditions under which influence is strongest. By randomly manipulating messages sent by adopters of a Facebook …

Using Facebook And Other Snss In K-12 Classrooms: Ethical Considerations For Safe Social Networking, Keith Howard

Education Faculty Articles and Research

The purpose of this article is to examine the potential risks of bringing social networking sites (SNS) into the classroom through the lens of Moor's (1999) just-consequentialist theory. Moor compares the setting of ethical policies in the fast-changing world of technology to a sailor trying to set a course while sailing. His analogy could not be more appropriate for educators' attempts to cope with the question of online social networking in schools. Educators must weigh the potential advantages of using SNSs in educational settings against the risks that such inclusion would entail. If the proper precautions are not taken, student …

Facebook As An Instructional Tool In The Secondary Classroom: A Case Study, Stephanie Hunter-Brown

Doctoral Dissertations and Projects

The purpose of this study is to describe how social media networks impact secondary students when utilized as an instructional tool . The problem this study seeks to address is exploring the roles that social media play in the lives of high school students and the experiences they encounter by utilizing these networks academically and socially. A case study approach was utilized to evaluate the impact of technology integration via social media networks in a secondary English classroom. The focus of the study was to determine the academic and social impact the social media network, more specifically Facebook, has on …

Prediction Of Topic Volume On Twitter, Yiye Ruan, Hemant Purohit, David Fuhry, Srinivasan Parthasarathy, Amit P. Sheth

Kno.e.sis Publications

We discuss an approach for predicting microscopic (individual) and macroscopic (collective) user behavioral patterns with respect to specific trending topics on Twitter. Going beyond previous efforts that have analyzed driving factors in whether and when a user will publish topic-relevant tweets, here we seek to predict the strength of content generation which allows more accurate understanding of Twitter users' behavior and more effective utilization of the online social network for diffusing information. Unlike traditional approaches, we consider multiple dimensions into one regression-based prediction framework covering network structure, user interaction, content characteristics and past activity. Experimental results on three large Twitter …

Trust Networks, Krishnaprasad Thirunarayan, Pramod Anantharam, Cory Andrew Henson, Amit P. Sheth

Kno.e.sis Publications

Trust relationships occur naturally in many diverse contexts such as collaborative systems, e-commerce, interpersonal interactions, social networks, semantic sensor web, etc. As collaborating agents providing content and services become increasingly removed from the agents that consume them, the issue of robust trust inference and update become critical. There is a need to find online substitutes for traditional (direct or face-to-face) cues to derive measures of trust, and create efficient and secure system for managing trust, to support decision-making. Unfortunately, there is neither a universal notion of trust that is applicable to all domains nor a clear explication of its semantics …

Identifying Social Influence In Networks Using Randomized Experiments, Sinan Aral, Dylan Walker

Business Faculty Articles and Research

The recent availability of massive amounts of networked data generated by email, instant messaging, mobile phone communications, micro blogs, and online social networks is enabling studies of population-level human interaction on scales orders of magnitude greater than what was previously possible.1'2 One important goal of applying statistical inference techniques to large networked datasets is to understand how behavioral contagions spread in human social networks. More precisely, understanding how people influence or are influenced by their peers can help us understand the ebb and flow of market trends, product adoption and diffusion, the spread of health behaviors such as smoking and …

Creating Social Contagion Through Viral Product Design: A Randomized Trial Of Peer Influence In Networks, Sinan Aral, Dylan Walker

Business Faculty Articles and Research

We examine how firms can create word-of-mouth peer influence and social contagion by designing viral features into their products and marketing campaigns. To econometrically identify the effectiveness of different viral features in creating social contagion, we designed and conducted a randomized field experiment involving the 1.4 million friends of 9,687 experimental users on Facebook.com. We find that viral features generate econometrically identifiable peer influence and social contagion effects. More surprisingly, we find that passive-broadcast viral features generate a 246% increase in peer influence and social contagion, whereas adding active-personalized viral features generate only an additional 98% increase. Although active-personalized viral …

Mobile Application Adoption By Young Adults: A Social Network Perspective, David G. Taylor, Troy A. Voelker, Iryna Pentina

WCBT Faculty Publications

The use of mobile applications, defined as small programs that run on a mobile device and perform tasks ranging from banking to gaming and web browsing, is exploding. Within the past two years, the industry has grown from essentially nothing to a $2 billion marketplace, but adoption rates are still on the rise. Using network theory, this study examines how the adoption of mobile apps among young consumers is influenced by others in their social network. The results suggest that the likelihood of adoption and usage of mobile apps increases with their use by the consumer's strongest relationship partner. In …

Trust Model For Semantic Sensor And Social Networks: A Preliminary Report, Pramod Anantharam, Cory Andrew Henson, Krishnaprasad Thirunarayan, Amit P. Sheth

Kno.e.sis Publications

Trust is an amorphous concept that is becoming Increasingly important in many domains, such as P2P networks, E-commerce, social networks, and sensor networks. While we all have an intuitive notion of trust, the literature is scattered with a wide assortment of differing definitions and descriptions; often these descriptions are highly dependent on a single domain or application of interest. In addition, they often discuss orthogonal aspects of trust while continuing to use the general term “trust”. In order to make sense of the situation, we have developed an ontology of trust that integrates and relates its various aspects into a …

Some Trust Issues In Social Networks And Sensor Networks, Krishnaprasad Thirunarayan, Pramod Anantharam, Cory Andrew Henson, Amit P. Sheth

Kno.e.sis Publications

Trust and reputation are becoming increasingly important in diverse areas such as search, e-commerce, social media, semantic sensor networks, etc. We review past work and explore future research issues relevant to trust in social/sensor networks and interactions. We advocate a balanced, iterative approach to trust that marries both theory and practice. On the theoretical side, we investigate models of trust to analyze and specify the nature of trust and trust computation. On the practical side, we propose to uncover aspects that provide a basis for trust formation and techniques to extract trust information from concrete social/sensor networks and interactions. We …

Artist Ranking Through Analysis Of On-Line Community Comments, Julia Grace, Daniel Gruhl, Kevin Haas, Meenakshi Nagarajan, Christine Robson, Nachiketa Sahoo

Kno.e.sis Publications

We describe an approach to measure the popularity of music tracks, albums and artists by analyzing the comments of music listeners in social networking online communities such as MySpace. This measure of popularity appears to be more accurate than the traditional measure based on album sales figures, as demonstrated by our focus group study. We faced many challenges in our attempt to generate a popularity ranking from the user comments on social networking sites, e.g., broken English sentences, comment spam, etc. We discuss the steps we took to overcome these challenges and describe an end to end system for generating …

Monetizing User Activity On Social Networks, Meenakshi Nagarajan, Kamal Baid, Amit P. Sheth, Shaojun Wang

Kno.e.sis Publications

In this work, we investigate techniques to monitize user activity on public forums, marketplaces and groups on social network sites. Our approach involves (a) identifying the monetization potential of user posts and (b) eliminating o- topic content in monetizable posts to use the most relevant keywords for advertising. Our first user study involving 30 users and data from MySpace and Facebook, shows that 52% of ad impressions shown after using our system were more targeted compared to the 30% relevant impressions generated without using our system. A second smaller study suggests that profile ads that are based on user activity …

Semantic Convergence Of Wikipedia Articles, Christopher J. Thomas, Amit P. Sheth

Kno.e.sis Publications

Social networking, distributed problem solving and human computation have gained high visibility. Wikipedia is a well established service that incorporates aspects of these three fields of research. For this reason it is a good object of study for determining quality of solutions in a social setting that is open, completely distributed, bottom up and not peer reviewed by certified experts. In particular, this paper aims at identifying semantic convergence of Wikipedia articles; the notion that the content of an article stays stable regardless of continuing edits. This could lead to an automatic recommendation of good article tags but also add …