Identifying influential user communities on the social network

Hu, Weishu; Gong, Zhiguo; U, Leong Hou; Guo, Jingzhi

doi:10.1080/17517575.2013.804586

Cited by 22 publications

(10 citation statements)

References 25 publications

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“…At the same time, they are able to accurately analyze hot search sensitive words, to explore and process new topics, and may also to process image . They are able to complete the quality of the community's content and maintain loyal fans, attract new fans [11], etc., to promote the healthy operation of the community.…”

Section: Cultivating Community E-commerce Operation Talentsmentioning

confidence: 99%

Research on the Current Situation and Development of Community E-commerce

Wang¹,

Peng²,

Zhang³

2018

Proceedings of the 2018 2nd International Conference on Economic Development and Education Management (ICEDEM 2018)

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With the continuous development of social media, the economic form based on social relationships has developed rapidly, and network red economy and fan economy have developed rapidly. This paper expounds the basic concepts of community e-commerce and the development trend of ecommerce in China, and analyzes the advantages and disadvantages of community e-commerce. In particular, it summarizes the problems existing in brand building, fan maintenance, operation and consumption habits during the development of community e-commerce, and proposes solutions to related problems in terms of building cultural systems, product positioning, and operational skills. It has seized the mainstream development direction of community e-commerce economy and provided relevant research directions for relevant practitioners.

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Section: Cultivating Community E-commerce Operation Talentsmentioning

confidence: 99%

Research on the Current Situation and Development of Community E-commerce

Wang¹,

Peng²,

Zhang³

2018

Proceedings of the 2018 2nd International Conference on Economic Development and Education Management (ICEDEM 2018)

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“…The work [14] analyzed influence in social groups within content-sharing based social networks, with an examination of the process of joining of users. Similarly, work in [15] also focused on detecting groups of users with common interests rather than studying their influence. [16] proposed a model of influence based on topic, investigating both direct and indirect influence, but not dealing with communities.…”

Section: Communitiesmentioning

confidence: 99%

Time-Dependent Influence Measurement in Citation Networks

Rakoczy¹,

Bouzeghoub²,

Gançarski³

et al. 2018

CSIMQ

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In every scientific discipline, researchers face two common dilemmas: where to find bleeding-edge papers and where to publish their own articles. We propose to answer these questions by looking at the influence between communities, e.g. conferences or journals. The influential conferences are those which papers are heavily cited by other conferences, i.e. they are visible, significant and inspiring. For the task of finding such influential places-to-publish, we introduce a Running Influence model that aims to discover pairwise influence between communities and evaluate the overall influence of each considered community. We have taken into consideration time aspects such as intensity of papers citations over time and difference of conferences starting years. The community influence analysis is tested on real-world data of Computer Science conferences.

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“…They observe that the users typically pay more attention to those users who share similar interests, which enable a way to partition the users into different communities according to their common interests. They propose two algorithms to detect influential communities using common interests in large social networks efficiently and effectively [7]. In our understanding, social networks and community research will be more and more popular in the future for many electronic commerce systems, such as Amazon, Alibaba, Facebook and Twitter, have provided services which allow users to form social networks to share and disseminate their ideas and views about items through the systems.…”

Section: Data Science and Social Networkingmentioning

confidence: 99%

On Enterprise Information System Research Trend<br/>—Based on the Keywords Frequency Analysis of Journal EIS 2007-2015

Wan¹,

Jiang²

2016

JSS

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The journal of Enterprise Information Systems (EIS) was founded in 2007 by Taylor & Francis, selected by the Web of Science Citation Index Expanded in 2008, and included in EI. The research collects 219 papers published in the EIS from 2007 to 2015, and explores valuable information such as the present situation and hotspot trends in the research of the enterprise information systems by extracting and analyzing the keyword of those papers. Finally, we analyze and comment on 9 related papers with considering the trends: enterprise architecture, cloud computing services, ontology and semantic, data science and social networking, enterprise integration and systems science. The research can help relevant scholars to understand EIS research situation, and have a mind to EIS research trends.

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Identifying influential user communities on the social network

Cited by 22 publications

References 25 publications

Research on the Current Situation and Development of Community E-commerce

Research on the Current Situation and Development of Community E-commerce

Time-Dependent Influence Measurement in Citation Networks

On Enterprise Information System Research Trend<br/>—Based on the Keywords Frequency Analysis of Journal EIS 2007-2015

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Identifying influential user communities on the social network

Cited by 22 publications

References 25 publications

Research on the Current Situation and Development of Community E-commerce

Research on the Current Situation and Development of Community E-commerce

Time-Dependent Influence Measurement in Citation Networks

On Enterprise Information System Research Trend&lt;br/&gt;—Based on the Keywords Frequency Analysis of Journal EIS 2007-2015

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Product

Resources

About

On Enterprise Information System Research Trend<br/>—Based on the Keywords Frequency Analysis of Journal EIS 2007-2015