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.     

A theoretical perspective on organizational culture and digitalization

Digitalization has fundamentally changed organizational structures and processes and affects how people interact with each other, thereby impacting organizational culture. Given the pervasiveness of digitalization today, it is useful to study its profound effects on organizational culture through new theoretical lenses. In this paper, we offer a fresh perspective on organizational culture in the digital world. We accomplish this by integrating two competing perspectives and then leveraging the new perspective to identify digital cultural resources and propose a conceptualization of digital culture. We frame our conceptualization around the cultural resources for digitalization and describe four digital culture archetypes.     

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 holistic perspective on the theoretical foundations for ICT4D research

ABSTRACT

While many theories have guided research Information and Communication Technologies for Development (ICT4D), we are yet to construct a clear and coherent narrative that would help us answer the question of how ICT fosters development in underdeveloped communities. In this paper, we argue that one of the main reasons for this is that our holistic understanding of ICT4D is seldom grounded in theories to understand the core areas that define the field, namely, ICT, Development, and, ‘4’ which are the transformative processes that link the two. Through a brief literature review, we list theories that have informed ICT4D research in each of these areas. We present examples of theories, namely, Capability Approach, Affordances, and Actor-Network Theory together with Social Capital and illustrate how we have used them in our research. Building on this holistic perspective on theoretical foundation, we propose five agendas for ICT4D research.     

System development effectiveness: An agency theory perspective

Agency theory can be used to explain the effectiveness of system development methods. As the cost of computing decreases and end user computing technology becomes feasible, end-user departments are developing their own application systems. Agency theory suggests that end-users will desire greater autonomy over their computing in order to avoid the agency costs that arise in traditional MIS development. This study provides empirical support for the proposition that user development allows end-user departments to minimize the agency costs resulting from the work of the MIS department. Data were collected from 162 users of 59 different applications in 30 organizations. The results indicate that user development is more effective than MIS development. Among user-developed application systems, departmental applications are more effective than corporate applications.     

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.     

基于博弈论的多车智能驾驶交互决策综述

智能驾驶是交通和汽车领域未来发展的重要方向,决策规划作为智能驾驶系统中的关键模块,一直是其重点研究领域之一.当前的研究热点正在从单车智能驾驶决策向混行交通场景下的多车智能驾驶决策进行拓展,因此,需要在复杂动态场景和多并行任务下生成符合车辆动力学且不与道路边界和其他交通参与者发生碰撞的高质量轨迹.多车混行驾驶是对道路时空资源的竞争性使用,博弈论可为多车交互决策提供重要的理论与技术手段.对此,应用博弈论方法进行智能驾驶决策研究的综述,基于滚动时域、微分博弈和马尔科夫博弈这3类常用的博弈模型,对现有相关研究进行归类总结和分析.首先简要介绍博弈论基础知识;其次,总结常见的智能驾驶场景并分析各场景下交互决策的核心问题;然后,通过3种不同的博弈模型对多车交互决策进行建模,分别介绍它们的求解算法和思路及相关的研究工作;最后,介绍相关的仿真实验和测试方法,同时也对未来的技术发展和挑战给出见解.     

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.     

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.     

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.     

Responses to ambivalence toward social networking sites: A typological perspective

A common assumption in prior research on social networking sites (SNS) has been that users' orientations toward SNS use are positioned somewhere along a bipolar, univalent continuum, stretching from negative to positive orientation. However, considering recent findings unfolding the intricacy and variety of SNS use patterns, such a linear conceptualization of users' orientations is too simplistic with limited ability to explain the intricate patterns of SNS use. To alleviate this deficiency in this paper, we draw on the ambivalence literature and explain that users can simultaneously experience both positive and negative orientations toward SNS use based on the positive and negative aspects of their SNS use experience. Focusing on post- adoptive SNS use context, we theorise archetypes of SNS users' attitudinal responses to ambivalence, and their associated behavioural outcomes in terms of SNS use patterns. We first follow a typological perspective and develop typologies of attitudinal and behavioural responses to ambivalence toward SNS use. Then, we offer six hypotheses that explain the relations between the archetypes of attitudinal responses to ambivalence toward SNS use and users' SNS use patterns. Lastly, we empirically test our hypotheses using latent profile analysis and ANCOVA applied to two-wave data collected from 370 ambivalent SNS users. The findings support the hypotheses and validate our typologies. The findings ultimately point to likely choices from a range of post-adoption SNS use patterns as plausible outcomes of SNS users' attitudinal responses to ambivalence.     

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.