278,330 research outputs found
Identifying Bridge Users: the Knowledge Transfer Agents in Enterprise Collaboration Systems
In recent years enterprise collaboration systems (ECS) integrated with social network capabilities have become popular tools for supporting knowledge management (KM) strategies and organizational learning. Increased usage has resulted in higher interest in understanding and classifying the roles that ECS users adopt online. Previous research has investigated user role identification by considering: the degree of participation in an ECS, the user interactions with shared content, the user role in the ECS network, and the user KM-role observed within an interaction. Although all of these factors provide insights into ECS user engagement, they fail to fully consider the knowledge sharing perspective. In this paper, we define bridge users within the context of KM and present a framework for identifying them using semantic analysis of user-generated content. Further, we present results and observations from tests of our pipeline on the ECS of a large multinational engineering company with more than 100k users
KNOWLEDGE SHARING IN A SMOKING CESSATION ONLINE COMMUNITY: A PRIVACY CALCULUS PERSPECTIVE
The paper presents a study design intended to disentangle the various components of social support and privacy concerns related to knowledge-sharing in a smoking cessation online health community from a privacy calculus perspective. In the research model, social support confers benefits of informational support, emotional support, esteem support, and network support, all of which have a positive effect on knowledge-sharing behaviour therein. The privacy concerns, articulated in terms of risks, entail threat appraisals (perceived severity and perceived vulnerability) and coping appraisals (response efficacy and self-efficacy). Threat appraisals negatively affect knowledge-sharing in the smoking cessation OHC, whereas coping appraisals have a positive effect on the sharing. Under privacy calculus theory, the risk-benefit analysis determines individual users’ knowledge-sharing behaviour in a smoking cessation OHC. The individual user’s smoking cessation OHC usage experience and the stage of smoking cessation are set as moderators in the proposed research model to explore user differences in knowledge sharing behaviour in the smoking cessation OHC. This study may contribute to a comprehensive understanding of the core antecedents to knowledge-sharing in smoking cessation OHCs
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Economic issues in distributed computing
textOn the Internet, one of the essential characteristics of electronic commerce is the integration of large-scale computer networks and business practices. Commercial servers are connected through open and complex communication technologies, and online consumers access the services with virtually unpredictable behavior. Both of them as well as the e-Commerce infrastructure are vulnerable to cyber attacks. Among the various network security problems, the Distributed Denial-of-Service (DDoS) attack is a unique example to illustrate the risk of commercial network applications. Using a massive junk traffic, literally anyone on the Internet can launch a DDoS attack to flood and shutdown an eCommerce website. Cooperative technological solutions for Distributed Denial-of-Service (DDoS) attacks are already available, yet organizations in the best position to implement them lack incentive to do so, and the victims of DDoS attacks cannot find effective methods to motivate the organizations. Chapter 1 discusses two components of the technological solutions to DDoS attacks: cooperative filtering and cooperative traffic smoothing by caching, and then analyzes the broken incentive chain in each of these technological solutions. As a remedy, I propose usage-based pricing and Capacity Provision Networks, which enable victims to disseminate enough incentive along attack paths to stimulate cooperation against DDoS attacks. Chapter 2 addresses possible Distributed Denial-of-Service (DDoS) attacks toward the wireless Internet including the Wireless Extended Internet, the Wireless Portal Network, and the Wireless Ad Hoc network. I propose a conceptual model for defending against DDoS attacks on the wireless Internet, which incorporates both cooperative technological solutions and economic incentive mechanisms built on usage-based fees. Cost-effectiveness is also addressed through an illustrative implementation scheme using Policy Based Networking (PBN). By investigating both technological and economic difficulties in defense of DDoS attacks which have plagued the wired Internet, our aim here is to foster further development of wireless Internet infrastructure as a more secure and efficient platform for mobile commerce. To avoid centralized resources and performance bottlenecks, online peer-to-peer communities and online social network have become increasingly popular. In particular, the recent boost of online peer-to-peer communities has led to exponential growth in sharing of user-contributed content which has brought profound changes to business and economic practices. Understanding the dynamics and sustainability of such peer-to-peer communities has important implications for business managers. In Chapter 3, I explore the structure of online sharing communities from a dynamic process perspective. I build an evolutionary game model to capture the dynamics of online peer-to-peer communities. Using online music sharing data collected from one of the IRC Channels for over five years, I empirically investigate the model which underlies the dynamics of the music sharing community. Our empirical results show strong support for the evolutionary process of the community. I find that the two major parties in the community, namely sharers and downloaders, are influencing each other in their dynamics of evolvement in the community. These dynamics reveal the mechanism through which peer-to-peer communities sustain and thrive in a constant changing environment.Information, Risk, and Operations Management (IROM
Online Popularity and Topical Interests through the Lens of Instagram
Online socio-technical systems can be studied as proxy of the real world to
investigate human behavior and social interactions at scale. Here we focus on
Instagram, a media-sharing online platform whose popularity has been rising up
to gathering hundred millions users. Instagram exhibits a mixture of features
including social structure, social tagging and media sharing. The network of
social interactions among users models various dynamics including
follower/followee relations and users' communication by means of
posts/comments. Users can upload and tag media such as photos and pictures, and
they can "like" and comment each piece of information on the platform. In this
work we investigate three major aspects on our Instagram dataset: (i) the
structural characteristics of its network of heterogeneous interactions, to
unveil the emergence of self organization and topically-induced community
structure; (ii) the dynamics of content production and consumption, to
understand how global trends and popular users emerge; (iii) the behavior of
users labeling media with tags, to determine how they devote their attention
and to explore the variety of their topical interests. Our analysis provides
clues to understand human behavior dynamics on socio-technical systems,
specifically users and content popularity, the mechanisms of users'
interactions in online environments and how collective trends emerge from
individuals' topical interests.Comment: 11 pages, 11 figures, Proceedings of ACM Hypertext 201
Web 2.0 and destination marketing: current trends and future directions
Over the last decade, destination marketers and Destination Marketing Organizations (DMOs) have increasingly invested in Web 2.0 technologies as a cost-effective means of promoting destinations online, in the face of drastic marketing budgets cuts. Recent scholarly and industry research has emphasized that Web 2.0 plays an increasing role in destination marketing. However, no comprehensive appraisal of this research area has been conducted so far. To address this gap, this study conducts a quantitative literature review to examine the extent to which Web 2.0 features in destination marketing research that was published until December 2019, by identifying research topics, gaps and future directions, and designing a theory-driven agenda for future research. The study’s findings indicate an increase in scholarly literature revolving around the adoption and use of Web 2.0 for destination marketing purposes. However, the emerging research field is fragmented in scope and displays several gaps. Most of the studies are descriptive in nature and a strong overarching conceptual framework that might help identify critical destination marketing problems linked to Web 2.0 technologies is missing
#mytweet via Instagram: Exploring User Behaviour across Multiple Social Networks
We study how users of multiple online social networks (OSNs) employ and share
information by studying a common user pool that use six OSNs - Flickr, Google+,
Instagram, Tumblr, Twitter, and YouTube. We analyze the temporal and topical
signature of users' sharing behaviour, showing how they exhibit distinct
behaviorial patterns on different networks. We also examine cross-sharing
(i.e., the act of user broadcasting their activity to multiple OSNs
near-simultaneously), a previously-unstudied behaviour and demonstrate how
certain OSNs play the roles of originating source and destination sinks.Comment: IEEE/ACM International Conference on Advances in Social Networks
Analysis and Mining, 2015. This is the pre-peer reviewed version and the
final version is available at
http://wing.comp.nus.edu.sg/publications/2015/lim-et-al-15.pd
Trends in crypto-currencies and blockchain technologies: A monetary theory and regulation perspective
The internet era has generated a requirement for low cost, anonymous and
rapidly verifiable transactions to be used for online barter, and fast settling
money have emerged as a consequence. For the most part, e-money has fulfilled
this role, but the last few years have seen two new types of money emerge.
Centralised virtual currencies, usually for the purpose of transacting in
social and gaming economies, and crypto-currencies, which aim to eliminate the
need for financial intermediaries by offering direct peer-to-peer online
payments.
We describe the historical context which led to the development of these
currencies and some modern and recent trends in their uptake, in terms of both
usage in the real economy and as investment products. As these currencies are
purely digital constructs, with no government or local authority backing, we
then discuss them in the context of monetary theory, in order to determine how
they may be have value under each. Finally, we provide an overview of the state
of regulatory readiness in terms of dealing with transactions in these
currencies in various regions of the world
EMERGING THE EMERGENCE SOCIOLOGY: The Philosophical Framework of Agent-Based Social Studies
The structuration theory originally provided by Anthony Giddens and the advance improvement of the theory has been trying to solve the dilemma came up in the epistemological aspects of the social sciences and humanity. Social scientists apparently have to choose whether they are too sociological or too psychological. Nonetheless, in the works of the classical sociologist, Emile Durkheim, this thing has been stated long time ago. The usage of some models to construct the bottom-up theories has followed the vast of computational technology. This model is well known as the agent based modeling. This paper is giving a philosophical perspective of the agent-based social sciences, as the sociology to cope the emergent factors coming up in the sociological analysis. The framework is made by using the artificial neural network model to show how the emergent phenomena came from the complex system. Understanding the society has self-organizing (autopoietic) properties, the Kohonen’s self-organizing map is used in the paper. By the simulation examples, it can be seen obviously that the emergent phenomena in social system are seen by the sociologist apart from the qualitative framework on the atomistic sociology. In the end of the paper, it is clear that the emergence sociology is needed for sharpening the sociological analysis in the emergence sociology
Using social media data to understand mobile customer experience and behavior
Understanding mobile customer experience and behavior is an important task for cellular service providers to improve the satisfaction of their customers. To that end, cellular service providers regularly measure the properties of their mobile network, such as signal strength, dropped calls, call blockage, and radio interface failures (RIFs). In addition to these passive measurements collected within the network, understanding customer sentiment from direct customer feedback is also an important means of evaluating user experience. Customers have varied perceptions of mobile network quality, and also react differently to advertising, news articles, and the introduction of new equipment and services. Traditional methods used to assess customer sentiment include direct surveys and mining the transcripts of calls made to customer care centers. Along with this feedback provided directly to the service providers, the rise in social media potentially presents new opportunities to gain further insight into customers by mining public social media data as well. According to a note from one of the largest online social network (OSN) sites in the US [7], as of September 2010 there are 175 million registered users, and 95 million text messages communicated among users per day. Additionally, many OSNs provide APIs to retrieve publically available message data, which can be used to collect this data for analysis and interpretation. Our plan is to correlate different sources of measurements and user feedback to understand the social media usage patterns from mobile data users in a large nationwide cellular network. In particular, we are interested in quantifying the traffic volume, the growing trend of social media usage and how it interacts with traditional communication channels, such as voice calls, text messaging, etc. In addition, we are interested in detecting interesting network events from users' communication on OSN sites and studying the temporal aspects - how the various types of user feedback behave with respect to timing. We develop a novel approach which combines burst detection and text mining to detect emerging issues from online messages on a large OSN network. Through a case study, our method shows promising results in identifying a burst of activities using the OSN feedback, whereas customer care notes exhibit noticeable delays in detecting such an event which may lead to unnecessary operational expenses. --Mobile customer experience,social media,text data mining,customer feedback
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