How Deep Runs the Karma? Structural Holes and Social Capital in an Online Community

Social capital is important as both a mechanism for governing online communities and a product of the interaction in those communities. How networks of relationships in online communities are structured has important implications for how social capital may be generated. We examine a popular website, Slashdot, that uses a system by which users can declare relationships with other users, and also has an embedded reputation system, which they call user Karma. The role between user reputation levels and social network structures may indicate the types of social capital that can form. Using the concept of structural holes, we find that Slashdot users develop broad networks at lower levels of participation, and deep networks at higher levels of reputation

Cultivating Social Resources on Social Network Sites: Facebook Relationship Maintenance Behaviors and Their Role in Social Capital Processes

This study explores the relationship between perceived bridging social capital and specific Facebook‐enabled communication behaviors using survey data from a sample of U.S. adults (N=614). We explore the role of a specific set of Facebook behaviors that support relationship maintenance and assess the extent to which demographic variables, time on site, total and “actual” Facebook Friends, and this new measure (Facebook Relationship Maintenance Behaviors) predict bridging social capital. Drawing upon scholarship on social capital and relationship maintenance, we discuss the role of social grooming and attention‐signaling activities in shaping perceived access to resources in one's network as measured by bridging social capital.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/108031/1/jcc412078.pd

Follow the slash(dot): Effect of feedback on new members in an online community

ABSTRACT Many virtual communities involve ongoing discussions, with large numbers of users and established, if implicit rules for participation. As new users enter communities like this, both they and existing members benefit when new users learn the standards for participation. Slashdot is a news and discussion site that has developed a system of distributed moderation to provide feedback about the value of posts on their site. This study examines three explanations for how new users learn to participate in a digital community: learning transfer from previous experiences, observation of other members, and feedback from other members. We find that new user behavior is affected by a combination of their viewing behavior, the moderation feedback they receive, and replies to their comments

Factors in Fairness and Emotion in Online Case Resolution Systems

Courts are increasingly adopting online information and communication technology, creating a need to consider the potential consequences of these tools for the justice system. Using survey responses from 209 litigants who had recently used an online case resolution system, we investigate factors that influenced litigants’ experiences of fairness and emotional feelings toward court officials. Our results show that ease of using the online case resolution system, the outcome of the case, and a litigant’s perceptions of procedural justice are positively associated both with whether the litigant views the process as fair and whether the litigant ultimately feels positive emotions toward court officials. We also analyze the online explanations litigants offer in their arguments to courts and litigant answers to an open-ended question about their court experiences, and highlight design and practical implications for online systems seeking to improve access to justice

AAPOR Report on Big Data

In recent years we have seen an increase in the amount of statistics in society describing different phenomena based on so called Big Data. The term Big Data is used for a variety of data as explained in the report, many of them characterized not just by their large volume, but also by their variety and velocity, the organic way in which they are created, and the new types of processes needed to analyze them and make inference from them. The change in the nature of the new types of data, their availability, the way in which they are collected, and disseminated are fundamental. The change constitutes a paradigm shift for survey research.There is a great potential in Big Data but there are some fundamental challenges that have to be resolved before its full potential can be realized. In this report we give examples of different types of Big Data and their potential for survey research. We also describe the Big Data process and discuss its main challenges

Managing Children's Online Identities: How Parents Decide what to Disclose about their Children Online

ABSTRACT While extensive research has investigated the risks of children sharing their personal information online, little work has investigated the implications of parents sharing personal information about their children online. Drawing on 102 interviews with parents, we investigate how parents decide what to disclose about their children on social network sites (SNSs). We find that mothers take on the responsibility of sharing content about their children more than fathers do. Fathers are more restrictive about sharing to broad and professional audiences and are concerned about sharing content that could be perceived as sexually suggestive. Both mothers and fathers work to leverage affordances of SNSs to limit oversharing. Building on prior work, we introduce the concept of parental disclosure management, which describes how parents decide what to share about their children online. We also describe an emerging third shift of work that highlights the additional work parents take on to manage children's identities online. We conclude with theoretical and practical implications for designing SNSs to better support family life online

For What It's Worth: Humans Overwrite Their Economic Self-interest to Avoid Bargaining With AI Systems

As algorithms are increasingly augmenting and substituting human decision-making, understanding how the introduction of computational agents changes the fundamentals of human behavior becomes vital. This pertains to not only users, but also those parties who face the consequences of an algorithmic decision. In a controlled experiment with 480 participants, we exploit an extended version of two-player ultimatum bargaining where responders choose to bargain with either another human, another human with an AI decision aid or an autonomous AI-system acting on behalf of a passive human proposer. Our results show strong responder preferences against the algorithm, as most responders opt for a human opponent and demand higher compensation to reach a contract with autonomous agents. To map these preferences to economic expectations, we elicit incentivized subject beliefs about their opponent's behavior. The majority of responders maximize their expected value when this is line with approaching the human proposer. In contrast, responders predicting income maximization for the autonomous AI-system overwhelmingly override economic self-interest to avoid the algorithm

The new SIGCHI EC's values and strategic initiatives.

The SIGCHI EC has articulated the following 10 values. Specifically, these are instrumental values: They are our preferred methods of behavior. They are not an end goal, but they translate into a means by which an end goal is accomplished