Echoes of power: Language effects and power differences in social interaction

Understanding social interaction within groups is key to analyzing online communities. Most current work focuses on structural properties: who talks to whom, and how such interactions form larger network structures. The interactions themselves, however, generally take place in the form of natural language --- either spoken or written --- and one could reasonably suppose that signals manifested in language might also provide information about roles, status, and other aspects of the group's dynamics. To date, however, finding such domain-independent language-based signals has been a challenge. Here, we show that in group discussions power differentials between participants are subtly revealed by how much one individual immediately echoes the linguistic style of the person they are responding to. Starting from this observation, we propose an analysis framework based on linguistic coordination that can be used to shed light on power relationships and that works consistently across multiple types of power --- including a more "static" form of power based on status differences, and a more "situational" form of power in which one individual experiences a type of dependence on another. Using this framework, we study how conversational behavior can reveal power relationships in two very different settings: discussions among Wikipedians and arguments before the U.S. Supreme Court.Comment: v3 is the camera-ready for the Proceedings of WWW 2012. Changes from v2 include additional technical analysis. See http://www.cs.cornell.edu/~cristian/www2012 for data and more inf

Análise de opiniões expressas nas redes sociais

As redes sociais são cada vez mais utilizadas no nosso dia-a-dia. O recente aumento de popularidade deste tipo de serviço veio trazer novas funcionalidades e aplicações. Os utilizadores contribuem com as suas opiniões e conhecimentos, formando um repositório de informação de grandes proporções. Esta informação é cada vez mais utilizada por empresas, que vêem nas redes sociais uma forma de promover os seus produtos junto do público ou analisar de que forma os mesmos são considerados. O estudo apresentado neste artigo aplicou técnicas de Análise Sentimental para verificar se a informação existente em duas redes sociais (Facebook e Twitter) pode ser utilizada para estimar valores que podem vir a ser obtidos na comercialização de bens ou serviços a serem lançados no mercado.The social networks have been increasingly used. Their popularity brought new features and applications. In social networks users contribute with their opinions and knowledge, forming a huge information repository. The use of this information by companies, which consider social networks as a way of promoting their products, has been rising. This study, through the use of Sentimental Analysis, sustain the conclusion that the information obtained from social networks (Facebook and Twitter) can be used to determine values that can be obtained in the commercialization of goods or services to be launched in the market

CAN YOU TRUST ONLINE RATINGS? EVIDENCE OF SYSTEMATIC DIFFERENCES IN USER POPULATIONS

Do user populations differ systematically in the way they express and rate sentiment? We use large collections of Danish and U.S. reviews to investigate this qustion, and we find evidence of important systematic differences: first, positive ratings are far more common in the U.S. data than in the Danish data. Second, Danish reviewers tend to under-rate their own positive reviews compared to U.S. reviewers. This has potentially far-reaching implications for the interpretation of user ratings, the use of which has exploded in recent year

Long-term Sequential and Temporal Dynamics in Online Consumer Ratings

Online consumer ratings provide important feedback for businesses and yield essential purchase information for consumers. Extant literature has recognized the importance of sequential and temporal dynamics of consumer ratings, but has shed light upon short-term dynamics (e.g., an initial decreasing rating trend) and lacks analyses of long-term dynamics. Existing findings thus cannot explain these long-term dynamics, which are particularly important as many items receive ratings over the long term. In this paper, we therefore examine long-term sequential and temporal dynamics in consumer ratings and in particular whether initial rating dynamics influence average ratings in the long-term. To do so, we apply regression models to an extensive long-term review dataset. First, we find and explain a new long-term sequentially increasing rating trend which leads to a U-shaped relationship between ratings and their order. Second, we reveal that strong initial rating dynamics have significant negative impact on long-term average ratings

An Investigation of the Expression and Rating of Sentiment

Do user populations differ systematically in the way they express and rate sentiment? We use large collections of Danish and U.S. film reviews to investigate this question, and we find evidence of important systematic differences: first, positive ratings are far more common in the U.S. data than in the Danish data. Second, highly positive terms occur far more frequently in the U.S. data. Finally, Danish reviewers tend to under-rate their own positive reviews compared to U.S. reviewers. This has potentially far-reaching implications for the interpretation of user ratings, the use of which has exploded in recent years

Evidence of Systematic Differences in User Populations

Do user populations differ systematically in the way they express and rate sentiment? We use large collections of Danish and U.S. reviews to investigate this question, and we find evidence of important systematic differences: first, positive ratings are far more common in the U.S. data than in the Danish data. Second, Danish reviewers tend to under-rate their own positive reviews compared to U.S. reviewers. This has potentially far-reaching implications for the interpretation of user ratings, the use of which has exploded in recent years

Reputation Failure: The Limits of Market Discipline in Consumer Markets

Many believe that consumersourced reputational information about products would increasingly replace topdown regulation Instead of protecting consumers through coercive laws reputational information gleaned from the wisdom of the crowd would guide consumer decision making There is now a growing pressure to deregulate in diverse fields such as contracts products liability consumer protection and occupational licensingbrbrThis Article presents a common failure mode of systems of reputation Reputation Failure By spotlighting the publicgood nature of reviews rankings and even gossip this Article shows the mismatch between the private incentives consumers have to create reputational information and its social value As a result of this divergence reputational information is beset by participation selection and social desirability biases that systematically distort it The Article argues that these distortions are inherent to most systems of reputation and that they make reputation far less reliable than traditionally understoodbrbrThe limits of reputation highlight the centrality of the law to the future of the marketplace Proper legal institutions can deal not only with the symptoms of reputation failure ” consumer mistakes ” but improve the flow and quality of reputational information thus correcting reputation failures before they arise The Article offers a general framework and explores a number of strategies A more robust system of reputation can preserve consumer autonomy without sacrificing consumer welfar

Tags de opinião

As tags podem ser utilizadas com diferentes propósitos, entre os quais organizar os recursos para fins pessoais e partilhar informação potencialmente relevante com outros utilizadores. Este trabalho conjuga diversas áreas de conhecimento e explora a utilização de tags, debruçando-se numa categoria em particular que engloba as tags de opinião. Estas podem ser usadas para expressar sentimentos ou opiniões sobre os recursos. Foram realizadas análises sobre a utilização de tags na loja online Amazon. Recolhida uma amostra de dados, as tags foram classificadas e analisadas segundo diversos aspectos, inclusive quanto à sua polaridade. Além da atribuição de tags, na Amazon é possível atribuir pontuações (de 1 a 5) aos recursos. Neste trabalho compararam-se ainda as duas formas referidas de classificação de recursos, verificando a existência de alguma correspondência entre ambas, com significado estatístico. Adicionalmente, foi desenvolvido um classificador semi-automático que tem como objectivo classificar as tags atribuídas aos recursos para proporcionar uma classificação rápida e eficiente da polaridade das tags que considera também a informação disponível sobre os recursos durante o processo.Tags can be used for different purposes, including organizing resources for personal use and sharing potentially relevant information with other users. This work combines several knowledge areas and explores the use of tags, in particular the opinion tags. These can be used to express feelings or opinions about the resources. Analyses were performed on the use of tags in the Amazon online store. After selecting a data sample, the tags were classified and analyzed according to various aspects, including their polarity. In addition to the allocation of tags in Amazon, scores (1-5) can be assigned to resources. This work also compared the two mentioned resource classification forms, checking for any correspondence between them, with a statistical significance. Additionally, we developed a semi-automatic classifier which aims to classify the tags assigned to resources to provide a fast and efficient classification of the polarity of the tags that also considers the available information on the resources during the process

On the Supply of Online Reviews: Volume, Valence, and Quality

University of Minnesota Ph.D. dissertation. May 2019. Major: Business Administration. Advisors: Alok Gupta, De Liu. 1 computer file (PDF); vii, 106 pages.UGC platforms such as Wikipedia, online review platforms, online Question and Answer forums have permeated many economic and societal activities and established their important roles in our lives. However, the secrets of enabling and sustaining the supply of UGC have only received limited attention. Needless to say, without a steady supply of quality content, UGC would not persist. My dissertation focuses on the supply of online reviews/ratings – a dominant source for consumers’ decision making. Volume, valence, and quality of online reviews are inter-related aspects. Accordingly, this dissertation consists of three chapters focusing on the three aspects. The first chapter explores whether friend contribution can be used to motivate users to write more and better reviews. The second chapter examines whether online ratings are robust to rating aberrations such as random ratings and fake ratings. The third chapter develops a measurement for assessing review quality and investigate the relationship of helpfulness votes (a commonly used proxy for review quality) with review quality