scholarly journals Managing the Flow of Information on an Enterprise Social Network

2017 ◽  
Vol 17 (3) ◽  
pp. 64-74
Author(s):  
M. Stul'
Keyword(s):  
Social Network ◽  
Enterprise Social Network ◽  
Flow Of Information

scholarly journals Pemanfaatan Social Network Analysis (SNA) Untuk Menganalisis Kolaborasi Panitia Pengawas Pilkada Tahun 2020 di Kecamatan Gunungpati Kota Semarang

2021 ◽  
Vol 14 (2) ◽  
pp. 244-255
Author(s):  
Lukman Santoso ◽  
Reni Veliyanti
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
High Category ◽  
Committee Network ◽  
Flow Of Information

The implementation of the 2020 Pilkada in Gunungpati District as a whole has improved in terms of the quality of its implementation. This is the result of the cooperation of all competent parties at the sub-district and village levels. This study aims to analyze the collaboration of the Supervisory Committee for the Election of Governors and Deputy Governors in 2020, Gunungpati District and to understand in depth the flow of information using Social Network Analysis (SNA). The results showed that the overall density of the supervisory committee network was 0.53 or 53%, so the characteristics of the network of members of the Panwaslu Kec.Gunungpati network were in the high category. Panwaslu members with the initials DAP, RV, WPU and M are the most dominant members of the Panwaslu with values of Centrality, Closeness and Betweness Centrality in the network.  

Enterprise social network (ESN) systems and knowledge sharing: what makes it work for users?

2019 ◽  
Vol 50 (2) ◽  
pp. 305-327
Author(s):  
Abhishek Kalra ◽  
Rupashree Baral
Keyword(s):  
Social Network ◽  
Knowledge Sharing ◽  
Structural Equation ◽  
Least Squares Method ◽  
Equation Modeling ◽  
Top Management ◽  
Management Support ◽  
Cross Sectional ◽  
Content Type ◽  
Enterprise Social Network

Purpose Enterprise Social Network (ESN) systems have emerged as the technology of choice to bolster and support organizational efforts for harnessing embedded knowledge. However, a lack of understanding about it limits the optimization of its potential. Hence, this paper aims to assess the role of hedonic motivation, network externalities (NE) and top management support in conjugation with the unified theory of acceptance and use of technology theory to understand ESN’s usage for knowledge sharing. Design/methodology/approach Data were collected from 187 ESN users through a survey questionnaire and subsequently analyzed using variance-based structural equation modeling using the partial least squares method. Findings ESNs are used both for utilitarian and hedonic purposes. Furthermore, the results also bring out the importance of externalities arising from an extensive network of users and complimentary services, as well as support regarding resources and recognition from the top management toward reinforcing the benefits of using ESNs. Research limitations/implications This study advances earlier knowledge by assessing the actual usage of ESNs for knowledge sharing. It takes into consideration multiple input variables, namely, performance expectancy, effort expectancy, NE amongst others to best resonate with the key factors driving its adoption and usage by an individual. However, because of the cross-sectional research design, causality can only be inferred. Practical implications The organizations are recommended to have in place the measures for attaining optimal usage of ESNs, and in turn, witness knowledge moves around in ways unfathomable. Steps should be taken to develop tools and ecosystems to provide users affordances for both increasing productivity, as well as opportunities for gaining pleasure. Originality/value This study is one of its kind effort to synthesize the knowledge about the ESNs in an Indian context. It provides fascinating insights into the determinants of intention and usage of ESNs for knowledge sharing.

scholarly journals Scratching a Niche: How Smaller Social Media Players Such as Dribbble Reflect the Viral Phenomenon

2019 ◽  
Vol 5 (4) ◽  
pp. 205630511989005 ◽  
Author(s):  
Jeff Hemsley ◽  
Rebecca D. Kelly
Keyword(s):  
Social Media ◽  
Social Network ◽  
Competitive Environment ◽  
Creative Industry ◽  
Social Phenomena ◽  
Network Site ◽  
Gig Economy ◽  
Number Of Factors ◽  
Social Media Site ◽  
Flow Of Information

Researchers have been studying the viral flow of information since the late 1990s, but this work has mainly focused on big sites like Twitter and Facebook. However, to comprehensively explore social phenomena such as virality requires us to look beyond the dominant networks. This study addresses this by looking at how users think about virality on Dribbble, a social network site with around 600,000 users that was created in 2009 for designers to showcase and get feedback on their work and to connect clients to design talent. Interviews confirm that viral-like events do exist on Dribbble. Our informants suggest that what spreads on Dribbble are elements of design (e.g., color palettes, line styles, textures), and they identify a number of factors they believe drive these viral-like events, which are the same kinds of factors that drive virality on larger sites. We briefly discuss how Dribbble feeds the gig economy in the creative industry and how virality becomes an important path for designers in a competitive environment. This work makes a contribution to the study of virality by focusing a small niche social media site and by looking at how users perceive and think about viral events.

Identifying target audience on enterprise social network

2019 ◽  
Vol 119 (1) ◽  
pp. 111-128 ◽  
Author(s):  
Jianhong Luo ◽  
Xuwei Pan ◽  
Shixiong Wang ◽  
Yujing Huang
Keyword(s):  
Social Media ◽  
Social Network ◽  
Latent Dirichlet Allocation ◽  
Topic Model ◽  
Information Service ◽  
Target Audience ◽  
Business Practices ◽  
Content Type ◽  
Enterprise Social Media ◽  
Enterprise Social Network

Purpose Delivering messages and information to potentially interested users is one of the distinguishing applications of online enterprise social network (ESN). The purpose of this paper is to provide insights to better understand the repost preferences of users and provide personalized information service in enterprise social media marketing. Design/methodology/approach It is accomplished by constructing a target audience identification framework. Repost preference latent Dirichlet allocation (RPLDA) topic model topic model is proposed to understand the mass user online repost preferences toward different contents. A topic-oriented preference metric is proposed to measure the preference degree of individual users. And the function of reposting forecasting is formulated to identify target audience. Findings The empirical research shows the following: a total of 20 percent of the repost users in ESN represent the key active users who are particularly interested in the latent topic of messages in ESN and fits Pareto distribution; and the target audience identification framework can successfully identify different target key users for messages with different latent topics. Practical implications The findings should motivate marketing managers to improve enterprise brand by identifying key target audience in ESN and marketing in a way that truthfully reflects personalized preferences. Originality/value This study runs counter to most current business practices, which tend to use simple popularity to seek important users. Adaptively and dynamically identifying target audience appears to have considerable potential, especially in the rapidly growing area of enterprise social media information service.

Raising your Eminence inside the Enterprise Social Network

2016 ◽  
Author(s):  
Shiri Kremer-Davidson ◽  
Inbal Ronen ◽  
Lior Leiba ◽  
Avi Kaplan ◽  
Maya Barnea
Keyword(s):  
Social Network ◽  
Enterprise Social Network

scholarly journals Identifying Social Media Influencers using Graph Analytics

2020 ◽  
Author(s):  
Pankti Joshi ◽  
Sabah Mohammed
Keyword(s):  
Social Media ◽  
Community Structure ◽  
Social Network ◽  
Network Analysis ◽  
Unstructured Data ◽  
Graph Analytics ◽  
Content Sharing ◽  
Twitter Data ◽  
Data Graph ◽  
Flow Of Information

<div>Social network analysis has been an essential topic</div><div>with broad content sharing from social media. Defining the</div><div>directed links in social media determine the flow of information and indicates the user’s influence. Due to the enormous data and unstructured nature of sharing information, there are several challenges caused while handling data. Graph Analytics proves to be an essential tool for addressing problems such as building networks from unstructured data, inferring information from the system, and analyzing the community structure of a network. The proposed approach aims to determine the influencers on Twitter data, based on the follower’s count as well as the retweet count. Several graph-based algorithms are implemented on the data collected to find the influencer as well as communities in the network.</div>

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