A behavioral perspective on social choice

We discuss what behavioral social choice can contribute to computational social choice. An important trademark of behavioral social choice is to switch perspective away from a traditional sampling approach in the social choice literature and to ask inference questions: Based on limited, imperfect, and highly incomplete observed data, what inference can we make about social choice outcomes at the level of a population that generated those observed data? A second important consideration in theoretical and behavioral work on social choice is model dependence: How do theoretical predictions and conclusions, as well as behavioral predictions and conclusions, depend on modeling assumptions about the nature of human preferences and/or how these preferences are expressed in ratings, rankings, and ballots of various kinds? Using a small subcollection from the Netflix Prize dataset, we illustrate these notions with real movie ratings from real raters. We highlight the key roles that inference and behavioral modeling play in the analysis of such data, particularly for sparse data like the Netflix ratings. The social and behavioral sciences can provide a supportive role in the effort to develop behaviorally meaningful and robust studies in computational social choice.     

Software agents and agency: A personal information management perspective

This paper considers the concept of agency and the applications of software agents within the field of Personal Information Management (PIM). PIM addresses the complex activities undertaken by individuals when organising their personal information. In the context of Personal Information Management, effective software agents may allow users to obtain information relevant to their tasks, and present it in a form that is directly targeted to the needs of the user.This paper concentrates on the notion of agency and its direct application to PIM tasks. A user-driven approach to the design of agent-based systems is presented. We argue that agent systems will only be successful if both usersand their tasks act as the bases for the design of such systems. An example task domain (searching the World-Wide Web) is introduced and a taxonomy of Web agents for the domain is discussed. Technical issues raised during the preliminary implementation of Web agents are also introduced.     

A game theoretical perspective on the quantum probabilities associated with a GHZ state

In the standard approach to quantum games, players’ strategic moves are local unitary transformations on an entangled state that is subsequently measured. Players’ payoffs are then obtained as expected values of the entries in the payoff matrix of the classical game on a set of quantum probabilities obtained from the quantum measurement. In this paper, we approach quantum games from a diametrically opposite perspective. We consider a classical three-player symmetric game along with a known expression for a set of quantum probabilities relevant to a tripartite Einstein–Podolsky–Rosen (EPR) experiment that depends on three players’ directional choices in the experiment. We define the players’ strategic moves as their directional choices in an EPR setting and then express their payoff relations in the resulting quantum game in terms of their directional choices, the entries of the payoff matrix, and the quantum probability distribution relevant to the tripartite EPR experiment.     

A game theoretical model for collaborative groups in social applications

In this paper, we address the problem of the free riding behaviour that takes advantage of collaborative educational social groups without contributing back to other participants posts. Free riders are active users who ask questions and draw knowledge from the community but provide very limited or no contributions back to it. Since the survival of a collaborative educational community is highly dependent on its active users and their contributions, motivating free riding users to take an active part would naturally augment the value the community provides and ensure its survivability. As a solution, we formally analyse the impact of the free riding behaviour by means of repeated game theory where classical and generous Tit for Tat are used. Such analysis shows the impact of such behaviour on educational communities and raises the need for other strategies that motivate free riding users to cooperate under the threat of being punished by cooperative ones; hence, we introduce reputation based Tit for Tat strategies. Our study suggests adding reputation as a parameter in users’ profiles in collaborative groups to improve their survivability.     

Large-margin minimum classification error training: A theoretical risk minimization perspective

Large-margin discriminative training of hidden Markov models has received significant attention recently. A natural and interesting question is whether the existing discriminative training algorithms can be extended directly to embed the concept of margin. In this paper, we give this question an affirmative answer by showing that the sigmoid bias in the conventional minimum classification error (MCE) training can be interpreted as a soft margin. We justify this claim from a theoretical classification risk minimization perspective where the loss function associated with a non-zero sigmoid bias is shown to include not only empirical error rates but also a margin-bound risk. Based on this perspective, we propose a practical optimization strategy that adjusts the margin (sigmoid bias) incrementally in the MCE training process so that a desirable balance between the empirical error rates on the training set and the margin can be achieved. We call this modified MCE training process large-margin minimum classification error (LM-MCE) training to differentiate it from the conventional MCE. Speech recognition experiments have been carried out on two tasks. First, in the TIDIGITS recognition task, LM-MCE outperforms the state-of-the-art MCE method with 17% relative digit-error reduction and 19% relative string-error reduction. Second, on the Microsoft internal large vocabulary telephony speech recognition task (with 2000 h of training data and 120 K words in the vocabulary), significant recognition accuracy improvement is achieved, demonstrating that our formulation of LM-MCE can be successfully scaled up and applied to large-scale speech recognition tasks.     

Digital movie piracy: A perspective on downloading behavior through social cognitive theory

This study refined and specified a model based on the application (e.g. LaRose & Kim, 2007) of social cognitive theory (Bandura, 1986) to analyze and compare the behavior and attitudes exhibited by movie downloaders and to compare the number of movies they consume. The model is tested against data obtained from college students and from attendees of a technological lifestyle forum in the Netherlands. After revisions, the model explained nearly 23% of the variance in the number of movies downloaded. The most important factors in this model were the drive to view many different and new movies, the social environment and perceived attitudes toward the behavior, and the degree to which downloading has embedded itself in the daily routine. Because the Dutch government and lobbyists are unclear about the current legislation in the Netherlands, a unique opportunity existed to study the impact of being aware of legislation on the behavior. The results also indicate an unexpected openness among the participants to an alternative film-distribution method in which both the producers and the consumers receive an honest deal. These findings suggest options for relieving the current political and social tensions associated with movie downloading without prosecuting an increasing portion of the population.     

Self-disclosure in Chinese micro-blogging: A social exchange theory perspective

This paper examines the influence of social benefits and costs on self-disclosure in the context of micro-blogging in China. Data were collected from 441 micro-blogging users, employing an online survey. Self-disclosure is measured in terms of amount, depth, honesty, intent, and valence of disclosure. The study found that relationship building, enjoyment and trust in service providers are positively related to self-disclosure, while perceived anonymity of self and perceived risk are negatively related to self-disclosure. However, convenience of relationship maintenance and self-presentation are not related to self-disclosure.     

Enterprise applications diffusion within organizations: A social learning perspective

We used a social learning explanation to explain the diffusion of an enterprise application (EA) within an organization. We viewed the implementation of EA as a pattern of key users’ behaviors to examine the effect of self-generated and external sources of influence. Such behavior is progressively developed over time. Our study was based on investigating two business areas in a single company. From our investigation, we determined that the key users’ behaviors toward EA diffusion were influenced by both cognitive factors and organizational stimuli. Although the organizational environment was similar for both sites, one area performed better than the other in diffusing the system.     

Knowledge-intensive systems in the social service agency: Anticipated impacts on the organisation

Shrinking resources and the increasing complexity of clinical decisions are stimulating research in knowledge-intensive computer applications for the delivery of social services. The expected benefits of knowledge-intensive applications such as expert systems include improvement in both the quality and the consistency of service delivery, augmentation of institutional memory, and reduced labour costs through greater reliance on paraprofessionals. This paper analyses the likely impacts of knowledge-intensive systems on social service organisations, drawing on trends in related service-delivery fields, and on known impacts of computer applications in organisations. A structural change may be anticipated: decision making and planning functions will shift increasingly from social service professionals to administrators.     

Modelling law using a feminist theoretical perspective 1

In recent years a schism has become apparent in artificial intelligence and law between those who claim that legal expert systems cannot be built without first establishing a satisfactory theoretical model of law ("purists") and those whose main desire is to build working systems with or without theoretical underpinning ("pragmatists"). Most attempts at finding a jurisprudential model for building expert systems, however, have inconclusively attempted to apply traditional “grand theories” and have embedded themselves in the long standing controversies of analytical jurisprudence. This paper highlights other theoretical possibilities for modelling law which have been sidelined in the AI and law field. In particular, it promotes the adoption of a feminist theoretical perspective on law and legal knowledge representation. Feminist legal critique has a discrete, concrete and pragmatic approach and so may be a good tool for the resolution of the demands of both purists and pragmatists. The paper applies these insights to a proposed child custody expert system.     

Congestion control in social-based sensor networks: A social network perspective

Social-based sensor networks are prone to congestion due to the limited storage space on each node and the unpredictable end-to-end delay. In this paper, we aim to develop an efficient congestion control approach from the social network perspective. For this purpose, we first identify the role of social ties in the process of congestion and specify a list of major congestion factors. Based on these factors, we then model the congestion control as a multiple attribute decision making problem (MADM), in which the weight of congestion factors is measured by an entropy method. We present a MADM-based congestion control approach that determines a set of forwarding messages and its transmission order on each encounter event. Moreover, we design a buffer management scheme that deletes messages whose removal would incur the least impact upon the network performance when the buffer overflows. Extensive real-trace driven simulation is conducted and the experimental results finally validate the efficiency of our proposed congestion control approach.     

On social computing research collaboration patterns: a social network perspective

The field of social computing emerged more than ten years ago. During the last decade, researchers from a variety of disciplines have been closely collaborating to boost the growth of social computing research. This paper aims at identifying key researchers and institutions, and examining the collaboration patterns in the field. We employ co-authorship network analysis at different levels to study the bibliographic information of 6 543 publications in social computing from 1998 to 2011. This paper gives a snapshot of the current research in social computing and can provide an initial guidance to new researchers in social computing.     

Knowledge sharing in online health communities: A social exchange theory perspective

Online health communities (OHC) are becoming valuable platforms for patients to communicate and find support. These communities are different from general online communities. The knowledge shared in an OHC can be categorized as either general (public) or specific (private), and each category is shared in vastly different ways. Using the social exchange theory, we propose a benefit vs. cost knowledge sharing model for OHCs. The benefits are mainly based on Maslow's hierarchy of needs, and the cost includes cognitive and executional costs. We use this benefit vs. cost model to examine how OHC members share general and specific knowledge. Data were collected from 323 users of two well-known OHCs in China and were analyzed using the structural equation model. The results demonstrate that three factors positively impact the sharing of both general and specific knowledge: a sense of self-worth, members’ perceived social support, and reputation enhancement. Another factor, face concern, has a negative influence on specific knowledge sharing and a positive influence on general knowledge sharing. Executional cost only negatively impacts general knowledge sharing, and cognitive cost only negatively impacts specific knowledge sharing. This study of OHCs reveals that personal benefits promote knowledge sharing and costs prohibit it. These impacts vary between general knowledge and specific knowledge sharing.     

The influence of role stress on self-disclosure on social networking sites: A conservation of resources perspective

There is a growing body of research about the influence of users’ perceived stress on their social networking site (SNS) usage behaviors. In general, stress negatively leads to a reduction in SNS usage (e.g., discontinuous use and self-disclosure). However, very little research has examined how SNS users strive to resolve stress problems from a positive perspective. To fill this gap, we conducted a research study among users of Moments, a large SNS in China. Based on the conservation of resources (COR) theory, we hypothesized that SNS users’ response to role stress, a subtype of stress, might be positive, leading to investments in social resources (e.g., motivation for relationship maintenance and self-presentation) and generating an increased level of self-disclosure on SNS. The survey results revealed the mediating effect of motivation for relationship maintenance and self-presentation on the SNS stress–disclosure relationship. We found that SNS users conserve their resources by maintaining relationships and presenting themselves positively in response to role stress, as predicted. Theoretical contributions and practical implications of the study are discussed, as are its limitations and directions for future research.     

Investigating recognition-based performance in an open content community: A social capital perspective

As the open source movement grows, it becomes important to understand the dynamics that affect the motivation of participants who contribute their time freely to such projects. One important motivation that has been identified is the desire for formal recognition in the open source community. We investigated the impact of social capital in participants’ social networks on their recognition-based performance; i.e., the formal status they are accorded in the community. We used a sample of 465 active participants in the Wikipedia open content encyclopedia community to investigate the effects of two types of social capital and found that network closure, measured by direct and indirect ties, had a significant positive effect on increasing participants’ recognition-based performance. Structural holes had mixed effects on participants’ status, but were generally a source of social capital.     

Determinants of users’ continuance of social networking sites: A self-regulation perspective

Social networking sites (SNS) have transformed how individuals interact, build and maintain social relationships. We proposed a research model on the determinants of user continuance using Bagozzi's framework of self-regulation as the theoretical foundation. Following the process of appraisal → emotional reactions → coping responses, we developed the model by leveraging findings from social presence and IS continuance research. Based on survey data from Facebook users, we found that appraisal factors (pleasure, awareness, connectedness, and system quality) were strong determinants of emotional reaction (user satisfaction and sense of belonging). User satisfaction and sense of belonging together positively influenced continuance intention.     

Social interaction and continuance intention in online auctions: A social capital perspective

This study explores how interaction within an online auction community affects online auction actor intention to continue trading with others. Adopting a social perspective drawing on social capital theory and IS literature, this study investigates how interactions among actors contribute to the creation and advancement of social capital. The analytical results demonstrate that the influence of user interaction on continuance intention in online auctions is mediated by the creation of various dimensions of social capital at the community level. Finally, the implications of the study findings are discussed.