scholarly journals Modeling Random Forwarding Actions for Information Diffusion over Mobile Social Networks

2016 ◽  
Vol 2016 ◽  
pp. 1-19 ◽  
Author(s):  
Ling Li ◽  
Min Liu ◽  
Weiming Shen ◽  
Guoqing Cheng
Keyword(s):  
Social Networks ◽  
Generating Function ◽  
Information Diffusion ◽  
Function Method ◽  
Mobile Social Networks ◽  
Interference Theory ◽  
Proposed Model ◽  
Novel Method ◽  
Types Of Information

Modeling information diffusion over social networks has attracted a lot of attention from both academia and industry. Based on universal generating function method and discrete stress-strength interference theory, a novel method is proposed to model the users’ random forwarding actions, and the most susceptible users are extracted. The effect of a user on information diffusion is quantified as node susceptibility (NS), and NS is defined as the probability that quantity of information (message) the user forwards is larger than that he receives. The model can address three questions: which users are most susceptible, which types of information they are most susceptible to, and when they are most susceptible. The solutions of these questions are very helpful for the practitioners. A case study is used to illustrate the feasibility and practicality of the proposed model.

Towards Information Diffusion in Mobile Social Networks

2016 ◽  
Vol 15 (5) ◽  
pp. 1292-1304 ◽  
Author(s):  
Zongqing Lu ◽  
Yonggang Wen ◽  
Weizhan Zhang ◽  
Qinghua Zheng ◽  
Guohong Cao
Keyword(s):  
Social Networks ◽  
Information Diffusion ◽  
Mobile Social Networks

scholarly journals Augmented Context-Based Conceptual User Modeling for Personalized Recommendation System in Online Social Networks

2020 ◽  
Vol 14 (3) ◽  
pp. 1-19
Author(s):  
Ammar Alnahhas ◽  
Bassel Alkhatib
Keyword(s):  
Social Networks ◽  
Online Social Networks ◽  
Recommendation System ◽  
Contextual Information ◽  
Detailed Comparison ◽  
Personalized Recommendation ◽  
User Models ◽  
Proposed Model ◽  
Recommendation Algorithms ◽  
Novel Method

As the data on the online social networks is getting larger, it is important to build personalized recommendation systems that recommend suitable content to users, there has been much research in this field that uses conceptual representations of text to match user models with best content. This article presents a novel method to build a user model that depends on conceptual representation of text by using ConceptNet concepts that exceed the named entities to include the common-sense meaning of words and phrases. The model includes the contextual information of concepts as well, the authors also show a novel method to exploit the semantic relations of the knowledge base to extend user models, the experiment shows that the proposed model and associated recommendation algorithms outperform all previous methods as a detailed comparison shows in this article.

scholarly journals Predictive Analytical Model for Microblogging Data Using Asset Bubble Modelling

2020 ◽  
Vol 14 (2) ◽  
pp. 108-118
Author(s):  
Srinidhi Hiriyannaiah ◽  
Siddesh G.M. ◽  
Srinivasa K.G.
Keyword(s):  
Social Media ◽  
Information Diffusion ◽  
Predictive Analytics ◽  
Heterogeneous Systems ◽  
Asset Bubble ◽  
Proposed Model ◽  
Different Types ◽  
Social Media Platforms ◽  
Types Of Information ◽  
Better Than

In recent days, social media plays a significant role in the ecosystem of the big data world and its different types of information. There is an emerging need for collection, monitoring, analyzing, and visualizing the different information from various social media platforms in different domains like businesses, public administration, and others. Social media acts as the representative with numerous microblogs for analytics. Predictive analytics of such microblogs provides insights into various aspects of the real-world entities. In this article, a predictive model is proposed using the tweets generated on Twitter social media. The proposed model calculates the potential of a topic in the tweets for the prediction purposes. The experiments were conducted on tweets of the regional election in India and the results are better than the existing systems. In the future, the model can be extended for analysis of information diffusion in heterogeneous systems.

Midstream social marketing and the co-creation of public services

2016 ◽  
Vol 6 (3) ◽  
pp. 277-293 ◽  
Author(s):  
Matthew Wood
Keyword(s):  
Social Networks ◽  
Social Marketing ◽  
Public Services ◽  
Service Providers ◽  
Content Type ◽  
Proposed Model ◽  
Service Staff ◽  
Client Relationships

Purpose This paper aims to highlight the importance of social marketing at the midstream (meso) level as a key component of a proposed model for co-creating public services. The model demonstrates how supportive relationships and conversations within and between service organisations, front-line service staff, social networks and clients are essential for the effective co-creation of health and welfare services and social marketing interventions. Design/methodology/approach This is a conceptual paper that uses network and services theory and a case study to show how the midstream social marketing approach and service co-creation can be applied in practice and how these concepts relate to upstream and downstream social marketing. Findings The case study demonstrates the powerful role of social networks, staff–client relationships and conversations in the co-creation of effective services and the improvement in communications, trust and understanding between service providers and the community. Practical implications The paper shows how service providers and social marketers can achieve co-created, customer-oriented services/interventions through the development of congruent, empathetic narratives, relationships and conversations. The case study demonstrates how this can be achieved in practice through staff training, the identification of “community communicators” and value-based targeting and communications. Originality/value The integration of conversations, relationships, values, services and midstream social marketing into a model for co-creation offers a valuable tool for social marketing and health/welfare service professionals.

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