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Opinion Mining and Sentiment Analysis
, 2008
"... An important part of our information-gathering behavior has always been to find out what other people think. With the growing availability and popularity of opinion-rich resources such as online review sites and personal blogs, new opportunities and challenges arise as people now can, and do, active ..."
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Cited by 711 (3 self)
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An important part of our information-gathering behavior has always been to find out what other people think. With the growing availability and popularity of opinion-rich resources such as online review sites and personal blogs, new opportunities and challenges arise as people now can, and do, actively use information technologies to seek out and understand the opinions of others. The sudden eruption of activity in the area of opinion mining and sentiment analysis, which deals with the computational treatment of opinion, sentiment, and subjectivity in text, has thus occurred at least in part as a direct response to the surge of interest in new systems that deal directly with opinions as a first-class object. This survey covers techniques and approaches that promise to directly enable opinion-oriented information-seeking systems. Our focus is on methods that seek to address the new challenges raised by sentiment-aware applications, as compared to those that are already present in more traditional fact-based analysis. We include materialon summarization of evaluative text and on broader issues regarding privacy, manipulation, and economic impact that the development of opinion-oriented information-access services gives rise to. To facilitate future work, a discussion of available resources, benchmark datasets, and evaluation campaigns is also provided.
A survey of trust and reputation systems for online service provision
, 2005
"... Trust and reputation systems represent a significant trend in decision support for Internet mediated service provision. The basic idea is to collect information about potential service providers in order to select the most reliable and trustworthy provider of services and information and to avoid th ..."
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Cited by 596 (14 self)
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Trust and reputation systems represent a significant trend in decision support for Internet mediated service provision. The basic idea is to collect information about potential service providers in order to select the most reliable and trustworthy provider of services and information and to avoid the less trustworthy. A natural side effect is that it also provides an incentive for good behaviour and therefore tends to have a positive effect on market quality. Reputation systems can be called collaborative sanctioning systems to reflect their collaborative nature, and are related to collaborative filtering systems. Reputation systems are already being used in successful commercial online applications. There is also a rapidly growing literature around trust and reputation systems, but unfortunately this activity is not very coherent. The purpose of this paper is to give an overview of existing and proposed systems that can be used to derive measures of trust and reputation for Internet transactions, to analyse the current trends and developments in this area, and to propose a research agenda for trust and reputation systems.
Propagation of Trust and Distrust
, 2004
"... A network of people connected by directed ratings or trust scores, and a model for propagating those trust scores, is a fundamental building block in many of today's most successful e-commerce and recommendation systems. In eBay, such a model of trust has significant influence on the price an i ..."
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Cited by 431 (1 self)
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A network of people connected by directed ratings or trust scores, and a model for propagating those trust scores, is a fundamental building block in many of today's most successful e-commerce and recommendation systems. In eBay, such a model of trust has significant influence on the price an item may command. In Epinions (epinions.com), conclusions drawn from the web of trust are linked to many behaviors of the system, including decisions on items to which each user is exposed. We develop a framework of trust propagation schemes, each of which may be appropriate in certain circumstances, and evaluate the schemes on a large trust network consisting of 800K trust scores expressed among 130K people. We show that a small number of expressed trusts/distrust per individual allows us to predict reliably trust between any two people in the system with high accuracy: a quadratic increase in actionable information. Our work appears to be the first to incorporate distrust in a computational trust propagation setting.
Combating web spam with trustrank
- In VLDB
, 2004
"... Web spam pages use various techniques to achieve higher-than-deserved rankings in a search engine’s results. While human experts can identify spam, it is too expensive to manually evaluate a large number of pages. Instead, we propose techniques to semi-automatically separate reputable, good pages fr ..."
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Cited by 403 (3 self)
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Web spam pages use various techniques to achieve higher-than-deserved rankings in a search engine’s results. While human experts can identify spam, it is too expensive to manually evaluate a large number of pages. Instead, we propose techniques to semi-automatically separate reputable, good pages from spam. We first select a small set of seed pages to be evaluated by an expert. Once we manually identify the reputable seed pages, we use the link structure of the web to discover other pages that are likely to be good. In this paper we discuss possible ways to implement the seed selection and the discovery of good pages. We present results of experiments run on the World Wide Web indexed by AltaVista and evaluate the performance of our techniques. Our results show that we can effectively filter out spam from a significant fraction of the web, based on a good seed set of less than 200 sites. 1
A survey of peer-to-peer content distribution technologies
- ACM Computing Surveys
, 2004
"... Distributed computer architectures labeled “peer-to-peer ” are designed for the sharing of computer resources (content, storage, CPU cycles) by direct exchange, rather than requiring the intermediation or support of a centralized server or authority. Peer-to-peer architectures are characterized by t ..."
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Cited by 369 (7 self)
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Distributed computer architectures labeled “peer-to-peer ” are designed for the sharing of computer resources (content, storage, CPU cycles) by direct exchange, rather than requiring the intermediation or support of a centralized server or authority. Peer-to-peer architectures are characterized by their ability to adapt to failures and accommodate transient populations of nodes while maintaining acceptable connectivity and performance. Content distribution is an important peer-to-peer application on the Internet that has received considerable research attention. Content distribution applications typically allow personal computers to function in a coordinated manner as a distributed storage medium by contributing, searching, and obtaining digital content. In this survey, we propose a framework for analyzing peer-to-peer content distribution technologies. Our approach focuses on nonfunctional characteristics such as security, scalability, performance, fairness, and resource management potential, and examines the way in which these characteristics are reflected in—and affected by—the architectural design decisions adopted by current peer-to-peer systems. We study current peer-to-peer systems and infrastructure technologies in terms of their distributed object location and routing mechanisms, their approach to content replication, caching and migration, their support for encryption, access control, authentication and identity, anonymity, deniability, accountability and reputation, and their use of resource trading and management schemes.
Trust management for the semantic web
- In ISWC
, 2003
"... Abstract. Though research on the Semantic Web has progressed at a steady pace, its promise has yet to be realized. One major difficulty is that, by its very nature, the Semantic Web is a large, uncensored system to which anyone may contribute. This raises the question of how much credence to give ea ..."
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Cited by 265 (3 self)
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Abstract. Though research on the Semantic Web has progressed at a steady pace, its promise has yet to be realized. One major difficulty is that, by its very nature, the Semantic Web is a large, uncensored system to which anyone may contribute. This raises the question of how much credence to give each source. We cannot expect each user to know the trustworthiness of each source, nor would we want to assign top-down or global credibility values due to the subjective nature of trust. We tackle this problem by employing a web of trust, in which each user provides personal trust values for a small number of other users. We compose these trusts to compute the trust a user should place in any other user in the network. A user is not assigned a single trust rank. Instead, different users may have different trust values for the same user. We define properties for combination functions which merge such trusts, and define a class of functions for which merging may be done locally while maintaining these properties. We give examples of specific functions and apply them to data from Epinions and our BibServ bibliography server. Experiments confirm that the methods are robust to noise, and do not put unreasonable expectations on users. We hope that these methods will help move the Semantic Web closer to fulfilling its promise. 1.
Robust Incentive Techniques for Peer-to-Peer Networks
, 2004
"... Lack of cooperation (free riding) is one of the key problems that confronts today's P2P systems. What makes this problem particularly difficult is the unique set of challenges that P2P systems pose: large populations, high turnover, asymmetry of interest, collusion, zero-cost identities, and tr ..."
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Cited by 253 (3 self)
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Lack of cooperation (free riding) is one of the key problems that confronts today's P2P systems. What makes this problem particularly difficult is the unique set of challenges that P2P systems pose: large populations, high turnover, asymmetry of interest, collusion, zero-cost identities, and traitors. To tackle these challenges we model the P2P system using the Generalized Prisoner's Dilemma (GPD), and propose the Reciprocative decision function as the basis of a family of incentives techniques. These techniques are fully distributed and include: discriminating server selection, maxflowbased subjective reputation, and adaptive stranger policies. Through simulation, we show that these techniques can drive a system of strategic users to nearly optimal levels of cooperation.
Predicting Positive and Negative Links in Online Social Networks
"... We study online social networks in which relationships can be either positive (indicating relations such as friendship) or negative (indicating relations such as opposition or antagonism). Such a mix of positive and negative links arise in a variety of online settings; we study datasets from Epinion ..."
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Cited by 225 (7 self)
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We study online social networks in which relationships can be either positive (indicating relations such as friendship) or negative (indicating relations such as opposition or antagonism). Such a mix of positive and negative links arise in a variety of online settings; we study datasets from Epinions, Slashdot and Wikipedia. We find that the signs of links in the underlying social networks can be predicted with high accuracy, using models that generalize across this diverse range of sites. These models provide insight into some of the fundamental principles that drive the formation of signed links in networks, shedding light on theories of balance and status from social psychology; they also suggest social computing applications by which the attitude of one user toward another can be estimated from evidence provided by their relationships with other members of the surrounding social network.
The digitization of word of mouth: Promise and challenges of online feedback mechanisms
- Management Science
, 2003
"... Online feedback mechanisms harness the bidirectional communication capabilities of the Internet to engineer large-scale, word-of-mouth networks. Best known so far as a technology for building trust and fostering cooperation in online marketplaces, such as eBay, these mechanisms are poised to have a ..."
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Cited by 191 (5 self)
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Online feedback mechanisms harness the bidirectional communication capabilities of the Internet to engineer large-scale, word-of-mouth networks. Best known so far as a technology for building trust and fostering cooperation in online marketplaces, such as eBay, these mechanisms are poised to have a much wider impact on organizations. Their growing popularity has potentially important implications for a wide range of management activities such as brand building, customer acquisition and retention, product development, and quality assurance. This paper surveys our progress in understanding the new possibilities and challenges that these mechanisms represent. It discusses some important dimensions in which Internet-based feedback mechanisms differ from traditional word-of-mouth networks and surveys the most important issues related to their design, evaluation, and use. It provides an overview of relevant work in game theory and economics on the topic of reputation. It discusses how this body of work is being extended and combined with insights from computer science, management science, sociology, and psychology to take into consideration the special properties of online environments. Finally, it identifies opportunities that this new area presents for operations research/management science (OR/MS) research.
Free-Riding and Whitewashing in Peer-to-Peer Systems
- ANNUALWORKSHOP ON ECONOMICS AND INFORMATION SECURITY
, 2004
"... We devise a simple model to study the phenomenon of free-riding and the effect of free identities on user behavior in peer-to-peer systems. At the heart of our model is a strategic user of a certain type, an intrinsic and private parameter that reflects the user's generosity. The user decides w ..."
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Cited by 164 (2 self)
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We devise a simple model to study the phenomenon of free-riding and the effect of free identities on user behavior in peer-to-peer systems. At the heart of our model is a strategic user of a certain type, an intrinsic and private parameter that reflects the user's generosity. The user decides whether to contribute or free-ride based on how the current burden of contributing in the system compares to her type. We derive the emerging cooperation level in equilibrium and quantify the effect of providing free-riders with degraded service on the emerging cooperation. We find that this penalty mechanism is beneficial mostly when the "generosity level" of the society (i.e., the average type) is low. To quantify the social cost of free identities, we extend the model to account for dynamic scenarios with turnover (users joining and leaving) and with whitewashers: users who strategically leave the system and re-join with a new identity. We find that the imposition of penalty on all legitimate newcomers incurs a significant social loss only under high turnover rates in conjunction with intermediate societal generosity levels.
