Applying a multi-dimensional hedonic concept of intrinsic motivation on social tagging tools: A theoretical model and empirical validation

2019 | International Journal of Information Management | Citations: 0

Authors: Allam, Hesham; Bliemel, Michael; Spiteri, Louise; Blustein, James; Ali-Hassan, Hossam

Abstract: A B S T R A C TParticipation in and adding content to social tagging tools is i ... Expand

Abstract: A B S T R A C TParticipation in and adding content to social tagging tools is important for these tools to achieve their purpose of classifying and organizing information. Users of social tagging tools are driven to participate and add tags by extrinsic and intrinsic motivation. Extrinsic motivation is dominating research as a main predictor of why users use information systems. Social tagging tools, as a subset of social media tools, are distinguished by their unique social aspect that makes intrinsic motivation a potential driver for users to add tags to content. Intrinsic motivation, when applied to social tagging tools, could entail many shades that represent different users' motives for using such tools. In this paper, we add a rich concept of intrinsic motivation to include hedonism as a main predictor of users' behavior on social tagging tools. We empirically validate a previously proposed theoretical model of three dimensional concepts of hedonism with three components describing individuals' hedonic state when interacting with social tagging tools: explorability, curiosity, and enjoyment. After a robust and thorough data analysis using structured equation modeling, the results confirm our theoretical model and suggest using a richer concept of enjoyment to reflect a hedonic dimension when investigating intrinsic motivation with interactive social media tools. Our validated model could be the spark of new factors that have the potential to influence user acceptance of information systems in general and in social media tools. This research contributes to the development of attitude-behavior theories that could explain users' acceptance of dynamic web Collapse

Topics: social bookmark intrinsic motivation social media usage intention user acceptance

Methods: survey structural equation modeling partial least squares regression chi squared test theory development

Theories: technology acceptance model motivation theory

ATHiCC: An Anonymous, Asynchronous, Serverless Instant Messaging Protocol

2019 | HICSS | Citations: 0

Authors: Balchasan, Daniel F; Ozaniak, Michal; Khajuria, Samant; Schwartz, Yoav; Steffensen, Nicolai S; Sørensen, Lene T

Abstract: Instant messaging has become a main form of communication between people. The ab ... Expand

Abstract: Instant messaging has become a main form of communication between people. The ability to instantly send messages to each other, even when the recipient is offline, has become second nature and is taken for granted in modern society. However, this is not without a cost. In the case of instant messaging, that cost is privacy. Service providers use centralized servers to store these messages and can collect information using the messages ‘Metadata’ or even read the contents of messages. This paper presents a novel protocol, ATHiCC (Asynchronous Tor Hidden Chat Communication) [1] that allows private and anonymous communication that doesn't require a server, and yet is still able to support asynchronous communication. A simulator was implemented to test the protocol and performance under various network conditions and topologies. The results of the simulation predict high delivery rates and low delays in message delivery under most conditions, even in small network topologies. Collapse

Topics: online chat social media anonymity social network Digg

Methods: simulation statistical hypothesis test literature study design process

Catch me if you can: Online protests on sites powered by user-generated content

2017 | Information & Management | Citations: 0

Authors: Silva, Leiser; Panahi, Hesam

Abstract: This study concentrates on online protests in websites that rely on user-generat ... Expand

Abstract: This study concentrates on online protests in websites that rely on user-generated content. We develop a case study on Digg, a website powered by user-generated content that encounters backlash from their community. Through an interpretive analysis of the case we identify how the context and interactions among key players lead to what we call a “catch me if you can” game, where users and administrators of the website battle in an effort to outsmart and outmaneuver each other. The findings reveal a tension between users and administrators that intensifies during the protest, and should be considered carefully by site administrators. Collapse

Topics: Digg user-generated content website legal context internet technology

Methods: case study theoretical contribution literature study computational algorithm

Social emotion classification of short text via topic-level maximum entropy model

2016 | Information & Management | Citations: 0

Authors: Rao, Yanghui; Xie, Haoran; Li, Jun; Jin, Fengmei; Wang, Fu Lee; Li, Qing

Abstract: With the rapid proliferation of Web 2.0, the identification of emotions embedded ... Expand

Abstract: With the rapid proliferation of Web 2.0, the identification of emotions embedded in user-contributed comments at the social web is both valuable and essential. By exploiting large volumes of sentimental text, we can extract user preferences to enhance sales, develop marketing strategies, and optimize supply chain for electronic commerce. Pieces of information in the social web are usually short, such as tweets, questions, instant messages, messages, and news headlines. Short text differs from normal text because of its sparse word co-occurrence patterns, which hampers efforts to apply social emotion classification models. Most existing methods focus on either exploiting the social emotions of individual words or the association of social emotions with latent topics learned from normal documents. In this paper, we propose a topic-level maximum entropy (TME) model for social emotion classification over short text. TME generates topic-level features by modeling latent topics, multiple emotion labels, and valence scored by numerous readers jointly. The overfitting problem in the maximum entropy principle is also alleviated by mapping the features to the concept space. An experiment on real-world short documents validates the effectiveness of TME on social emotion classification over sparse words. Collapse

Topics: Twitter Digg social media electronic commerce big data

Methods: topic model computational algorithm experiment optimization model literature study

Analyzing and predicting news popularity on Twitter

2015 | International Journal of Information Management | Citations: 14

Authors: Wu, Bo; Shen, Haiying

Abstract: Twitter is not only a social network, but also an increasingly important news me ... Expand

Abstract: Twitter is not only a social network, but also an increasingly important news media. In Twitter, retweeting is the most important information propagation mechanism, and supernodes (news medias) that have many followers are the most important information sources. Therefore, it is important to understand the news retweet propagation from supernodes and predict news popularity quickly at the very first few seconds upon publishing. Such understanding and prediction will benefit many applications such as social media management, advertisement and interaction optimization between news medias and followers. In this paper, we identify the characteristics of news propagation from supernodes from the trace data we crawled from Twitter. Based on the characteristics, we build a news popularity prediction model that can predict the final number of retweets of a news tweet very quickly. Through trace-driven experiments, we then validate our prediction model by comparing our predicted popularity and real popularity, and show its superior performance in comparison with the regression prediction model. From the study, we found that the average interaction frequency between the retweeters and the news source is correlated with news popularity. Also, the negative sentiment of news has some correlations with retweet popularity while the positive sentiment of news does not have such obvious correlation. Collapse

Topics: Twitter application programming interface social network Digg usability

Methods: computational algorithm regression analysis method stochastic model optimization model machine learning method

Toward Effective Social Contagion: A Micro Level Analysis of the Impact of Dyadic Network Relationship

2014 | International Conference on Information Systems | Citations: 0

Authors: Peng, Jing; Agarwal, Ashish; Hosanagar, Kartik; Iyengar, Raghuram

Abstract: Social advertising holds the potential to reshape the traditional advertising in ... Expand

Abstract: Social advertising holds the potential to reshape the traditional advertising industry. Understanding what leads to effective social contagion at the dyadic level lies at the core of cost-effective social advertising strategies. This paper is the first attempt to comprehensively study the effect of dyadic network relationship on social contagion in directed networks. This paper reveals several intriguing findings of great importance to social media marketers: (1) reciprocal followers of adopters are less likely to be influenced than non-reciprocal followers, as moderated by the popularity and novelty of information; (2) social media users pay attention to their followers’ tastes while making the adoption decision; (3) the number of common mutual followers has opposite effects on the dyadic influence between reciprocal (positive) and non-reciprocal (negative) ties. In addition, this paper provides a novel model to identify social influence when adoption events are caused by multiple sources. Collapse

Topics: social media Digg Twitter marketing management social influence

Methods: simulation proportional hazards model descriptive statistic theorem proofing optimization model

Theories: social contagion theory

Information privacy and correlates: an empirical attempt to bridge and distinguish privacy-related concepts

2013 | European Journal of Information Systems | Citations: 0

Authors: Dinev, Tamara; Xu, Heng; Smith, Jeff H.; Hart, Paul

Abstract: Privacy is one of the few concepts that has been studied across many disciplines ... Expand

Abstract: Privacy is one of the few concepts that has been studied across many disciplines, but is still difficult to grasp. The current understanding of privacy is largely fragmented and discipline-dependent. This study develops and tests a framework of information privacy and its correlates, the latter often being confused with or built into definitions of information privacy per se. Our framework development was based on the privacy theories of Westin and Altman, the economic view of the privacy calculus, and the identity management framework of Zwick and Dholakia. The dependent variable of the model is perceived information privacy. The particularly relevant correlates to information privacy are anonymity, secrecy, confidentiality, and control. We posit that the first three are tactics for information control; perceived information control and perceived risk are salient determinants of perceived information privacy; and perceived risk is a function of perceived benefits of information disclosure, information sensitivity, importance of information transparency, and regulatory expectations. The research model was empirically tested and validated in the Web 2.0 context, using a survey of Web 2.0 users. Our study enhances the theoretical understanding of information privacy and is useful for privacy advocates, and legal, management information systems, marketing, and social science scholars. Collapse

Topics: privacy data breach anonymity information privacy concern web 2.0

Methods: survey statistical hypothesis test partial least squares regression structural equation modeling survey design

Theories: social sciences theory privacy calculus theory

Member engagement within digitally enabled social network communities: new methodological considerations

2013 | Information Systems Journal | Citations: 35

Authors: Germonprez, Matt; Hovorka, Dirk S.

Abstract: Digitally enabled social networks (DESN) are a complex assemblage of engagement, ... Expand

Abstract: Digitally enabled social networks (DESN) are a complex assemblage of engagement, reflection, action, technology, organization and community. DESN create a unique challenge for researchers who aim to understand what social networks are, what they can become and what enablers and constraints underlie trajectories of member engagement. As DESN continually evolve, knowing them as stable and reified representations or as mere technology artefacts provides a limited understanding of their complexity and emergent properties. While DESN are, in part, the technology that supports the necessary actions for engagement, they are also the people and behaviours that constitute its community. Through the presentation of new methodological considerations towards Digg, a large DESN, we observe that social networks entail practices of engagement, change and evolution within a DESN community. We reveal how engagement is a communal endeavour and that the clash of socio-technical trajectories can result in the emergence of new paths of member participation. Our findings demonstrate the potential of netnography and impressionist tales for contributing to the ongoing pluralistic investigations of DESN and also inform research on engagement and community design and change. Collapse

Topics: social network Digg Reddit Twitter innovation management

Methods: netnography theory development ethnography field study

Who will lead and who will follow: Identifying Influential Users in Online Social Networks: A Critical Review and Future Research Directions

2013 | Business & Information Systems Engineering | Citations: 7

Authors: Probst, Florian; Grosswiele, Laura; Pfleger, Regina

Abstract: One of the most important questions at the heart of viral marketing is how comp ... Expand

Abstract: One of the most important questions at the heart of viral marketing is how companies can identify and target the "right" initial set of influential users in Online Social Networks (OSN). Even though we find that both the scientific Business and Information Systems Engineering (BISE) and Marketing community engage in research on the identification of influential users in OSN, the development of practical approaches is still in its infancy. Therefore, we analyze and synthesize the growing number of scientific publications and hope that the results can stimulate and guide future research. Collapse

Topics: database system marketing management social network Digg Orkut

Methods: literature sample literature study computational algorithm synthesis structured literature research

News Recommender Systems with Feedback

2012 | International Conference on Information Systems | Citations: 0

Authors: Prawesh, Shankar; Padmanabhan, Balaji

Abstract: The focus of present research is widely used news recommendation techniques such ... Expand

Abstract: The focus of present research is widely used news recommendation techniques such as “most popular” or “most e-mailed”. In this paper we have introduced an alternative way of recommendation based on feedback. Various notable properties of the feedback based recommendation technique have been also discussed. Through simulation model we show that the recommendation technique used in the present research allows implementers to have a flexibility to make a balance between accuracy and distortion. Analytical results have been established in a special case of two articles using the formulation based on generalized urn models. Finally, we show that news recommender systems can be also studied through two armed bandit algorithms. Collapse

Topics: recommender system website advertising management Digg

Methods: simulation computational algorithm literature sample machine learning theoretical contribution