scholarly journals Can Dynamic Knowledge-Sharing Activities Be Mirrored From the Static Online Social Network in Yahoo! Answers and How to Improve Its Quality of Service?

2017 ◽  
Vol 47 (12) ◽  
pp. 3363-3376 ◽  
Author(s):  
Haiying Shen ◽  
Guangyan Wang
Keyword(s):  
Quality Of Service ◽  
Social Network ◽  
Knowledge Sharing ◽  
Online Social Network

scholarly journals Identification of Influencers in eWord-of-Mouth communities using their Online Participation Features

2016 ◽  
Author(s):  
Sergio L. Toral ◽  
Maria Olmedilla ◽  
Francisco José Arenas-Márquez ◽  
M. Rocio Martinez-Torres
Keyword(s):  
Social Network ◽  
Online Social Network ◽  
Experimental Results ◽  
Purchasing Decisions ◽  
Trust Network ◽  
Online Participation ◽  
Meaningful Information

The identification of influencers in any type of online social network is of paramount importance, as they can significantly affect consumers’ purchasing decisions. This paper proposes the utilization of a self-designed web scraper to extract meaningful information for the identification of influencers and the analysis of how this new set of variables can be used to predict them. The experimental results from the Ciao UK website will be used to illustrate the proposed approach and to provide new insights in the identification of influencers. Obtained results show the importance of the trust network, but considering the intensity and the quality of both trustors and trustees.

Continuous Knowledge Sharing in Online Social Network Communities

2012 ◽  
pp. 228-247
Author(s):  
Stella W. Tian
Keyword(s):  
Social Capital ◽  
Social Network ◽  
Knowledge Sharing ◽  
Online Social Network ◽  
Three Dimensions ◽  
Network Services ◽  
Community Members ◽  
Social Mechanism ◽  
Dynamic Interactions ◽  
Network Communities

Drawing upon Jasperson, Carter, and Zmud’s feature-centric view of technology (Jasperson, Carter, & Zmud, 2005) and Nahapiet and Ghoshal’s three dimensions of social capital factors (Nahapiet & Ghoshal, 1998), this chapter develops a conceptual model to elaborate the dynamic interactions between Social Network Services (SNS) features, social capital factors, and motivational antecedents on continuous participation in knowledge sharing activities among Online Social Network (OSN) community members. A number of SNS features, social capital factors, and motivational antecedents are set forth in this chapter. And the mechanism that links these factors is reviewed. It is proposed that, with embedded social mechanism, SNS features can strengthen motivations to continued participation through social capital facilitators.

scholarly journals How Does User Social Network Improve Innovation Outcomes on a Virtual Innovation Platform?

2021 ◽  
Vol 29 (3) ◽  
pp. 188-211
Author(s):  
Guijie Qi ◽  
Linke Hou ◽  
Jiali Chen ◽  
Yikai Liang ◽  
Qi Zhang
Keyword(s):  
Social Network ◽  
Emotional Support ◽  
Positive Emotions ◽  
Online Social Network ◽  
User Innovation ◽  
Positive Effects ◽  
Quality Dimensions ◽  
Innovation Platform ◽  
Innovation Outcomes

Previous studies demonstrate that online interactive relations can help improve users' innovation outcomes, yet few studies have investigated how they influence user innovation. This paper builds a social network based on users' online interactive relations in one virtual innovation platform (LEGO Ideas). It characterizes the online social network relations from both quantity and quality dimensions and examines their influencing paths on users' innovation outcomes (i.e., emotional support and information flow). The empirical results show that both the quantity and quality of online relations impose positive effects on innovation, yet in different ways. The quantity of online relations could bring users more positive emotions, whereas the quality of online relations could bring them with more useful information and knowledge. By examining the influencing paths, this paper contributes to the literature on how online relations influence innovation outcomes as well as provides practical suggestions for innovation platforms.

Knowledge sharing discourse types used by key actors in online affinity spaces

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Priya Sharma ◽  
Qiyuan Li ◽  
Susan M. Land
Keyword(s):  
Social Network ◽  
Knowledge Sharing ◽  
Sentiment Analysis ◽  
Online Social Network ◽  
Rule Mining ◽  
Content Type ◽  
Network Analyses ◽  
Affinity Spaces ◽  
Highly Active ◽  
Affinity Space

Purpose The growth of online social network sites and their conceptualization as affinity spaces makes them well suited for exploring how individuals share knowledge and practices around specific interests or affinities. The purpose of this study is to extend what is known about highly active/key actors in online affinity spaces, especially the ways in which they sustain and contribute to knowledge sharing. Design/methodology/approach This study analyzed 514 discussion posts gathered from an online affinity space on disease management. This study used a variety of methods to answer the research questions: the authors used discourse analyses to examine the conversations in the online affinity space, social network analyses to identify the structure of participation in the space and association rule mining and sentiment analysis to identify co-occurrence of discourse codes and sentiment of the discussions. Findings The results indicate that the quality and type of discourse varies considerably between key and other actors. Key actors’ discourse in the network serves to elaborate on and explain ideas and concepts, whereas other actors provide a more supportive role and engage primarily in storytelling. Originality/value This work extends what is known about informal mentoring and the role of key actors within affinity spaces by identifying specific discourse types and types of knowledge sharing that are characteristic of key actors. Also, this study provides an example of the use of a combination of rule mining association and sentiment analysis to characterize the nature of the affinity space.

scholarly journals COMMENT ANALYSIS FOR PRODUCT AND SERVICE SATISFACTION FROM THAI CUSTOMERS' REVIEW IN SOCIAL NETWORK

2018 ◽  
Author(s):  
Todsanai Chumwatana
Keyword(s):  
Social Media ◽  
Quality Of Service ◽  
Social Network ◽  
Sentiment Analysis ◽  
Experimental Studies ◽  
Online Reviews ◽  
Huge Amount ◽  
Media Usage ◽  
The Social

In the last decade, the amount of social media usage has rapidly increased exponentially in Thailand. A huge amount of Thai online reviews and comments are available on social network every second. Because of this fact, comment analysis, also called sentiment analysis, has then become an essential task to analyze people’s emotions, opinion, attitudes and sentiments from the amount of these online posts. This paper proposed the technique for analyzing Thai customers’ comments or opinions about the products and services by counting the polarity words of the product and service domains. To demonstrate the proposed technique, experimental studies on analyzing Thai customers’ comments in the social media are presented in this paper. The comments are classified into neutral, positive or negative. The proposed technique benefits the business domain in guiding product improvement and quality of service. Hence, this paper also benefits the end-users in making a smart decision.

scholarly journals University campus social network system for knowledge sharing

2012 ◽  
Vol 9 (4) ◽  
pp. 1721-1737 ◽  
Author(s):  
Zhao Du ◽  
Xiaolong Fu ◽  
Can Zhao ◽  
Ting Liu ◽  
Qifeng Liu
Keyword(s):  
Social Network ◽  
Knowledge Sharing ◽  
Evaluation Method ◽  
Online Social Network ◽  
Network Services ◽  
Personalized Recommendation ◽  
Network System ◽  
University Campus ◽  
Digital Resources ◽  
Social Network Services

Public online social network services have achieved dazzling success in recent years. As a result, vertical social network services for universities are expected warmly by campus users. As the majority of activities in university campus are knowledge and social interaction intensive, one of the core functions of campus social network system is to facilitate knowledge sharing on campus. In the cyberspace of universities, knowledge is stored in various kinds of digital resources such as documents, photos, videos etc. In this paper, we discuss the design and implementation of our campus social network system, concentrating on knowledge sharing mechanism in the system. The knowledge sharing mechanism has five features including the utilization of users? personal social network to facilitate the dissemination of digital resources, the use of a six-tuple model based tagging to realize the unified labeling for digital resources, the fine-grained access control based on friend lists for safer knowledge sharing, the adoption of a multiscale evaluation method for digital resources and personalized recommendation for digital resource with social graph based collaborative filtering as its core idea. With all these considerations, we expect to improve the efficiency and effectiveness of knowledge while enlarging the dissemination scope of digital resources carrying it in cyberspace of universities.

Extraverts Have Larger Social Network Layers

2011 ◽  
Vol 32 (3) ◽  
pp. 161-169 ◽  
Author(s):  
Thomas V. Pollet ◽  
Sam G. B. Roberts ◽  
Robin I. M. Dunbar
Keyword(s):  
Social Network ◽  
Social Relationships ◽  
Outer Layer ◽  
Network Size ◽  
Emotional Intensity ◽  
Emotional Closeness ◽  
Network Layer ◽  
Network Layers ◽  
Social Network Size

Previous studies showed that extraversion influences social network size. However, it is unclear how extraversion affects the size of different layers of the network, and how extraversion relates to the emotional intensity of social relationships. We examined the relationships between extraversion, network size, and emotional closeness for 117 individuals. The results demonstrated that extraverts had larger networks at every layer (support clique, sympathy group, outer layer). The results were robust and were not attributable to potential confounds such as sex, though they were modest in size (raw correlations between extraversion and size of network layer, .20 < r < .23). However, extraverts were not emotionally closer to individuals in their network, even after controlling for network size. These results highlight the importance of considering not just social network size in relation to personality, but also the quality of relationships with network members.

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