scholarly journals Applying topic model combined with Kohonen networks to discover and visualize communities on social networks

2020 ◽  
Vol 3 (3) ◽  
pp. 311-326
Author(s):  
Ho Trung Thanh ◽  
Nguyen Quang Hung ◽  
Tran Duy Thanh
Keyword(s):  
Social Networks ◽  
Topic Model ◽  
Message Content ◽  
Online Newspapers ◽  
Online Groups ◽  
Network Communities ◽  
Kohonen Neural Networks ◽  
Research Goal ◽  
Kohonen Networks ◽  
Making Friends

Users are members of communities on social networks. Users’ interested topics keep changing, resulting in the change of their communities’ interested topics as well. Level, period of time, and interested topics represent features of a community which (i) change upon preferences of each user on social networks for making friends or being interested in topics (based on message content); (ii) are formed or change from online groups of friends or the suggestions to make friends. Hence, the link of users in communities can be viewed as a network of users by their features in social network communities. In this paper, the author studies and proposes a new model for discovering communities using Temporal-Author-Recipient-Topic (TART) model combined with Kohonen neural networks to discover communities of users with the same interested topics over different periods of time. The research goal is achieved through testing models on two Vietnamese datasets (collected from social networks at universities and online newspapers).  

scholarly journals Research on Sentiment Tendency and Evolution of Public Opinions in Social Networks of Smart City

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-13 ◽  
Author(s):  
Yanni Liu ◽  
Dongsheng Liu ◽  
Yuwei Chen
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Sentiment Analysis ◽  
Smart City ◽  
Topic Model ◽  
Rapid Development ◽  
Mobile Internet ◽  
Time Curve ◽  
Public Opinions ◽  
The Social

With the rapid development of mobile Internet, the social network has become an important platform for users to receive, release, and disseminate information. In order to get more valuable information and implement effective supervision on public opinions, it is necessary to study the public opinions, sentiment tendency, and the evolution of the hot events in social networks of a smart city. In view of social networks’ characteristics such as short text, rich topics, diverse sentiments, and timeliness, this paper conducts text modeling with words co-occurrence based on the topic model. Besides, the sentiment computing and the time factor are incorporated to construct the dynamic topic-sentiment mixture model (TSTS). Then, four hot events were randomly selected from the microblog as datasets to evaluate the TSTS model in terms of topic feature extraction, sentiment analysis, and time change. The results show that the TSTS model is better than the traditional models in topic extraction and sentiment analysis. Meanwhile, by fitting the time curve of hot events, the change rules of comments in the social network is obtained.

Computational modeling of Weibo user influence based on information interactive network

2016 ◽  
Vol 40 (7) ◽  
pp. 867-881 ◽  
Author(s):  
Dingguo Yu ◽  
Nan Chen ◽  
Xu Ran
Keyword(s):  
Social Networks ◽  
Computational Model ◽  
Large Scale ◽  
Mobile Internet ◽  
Activity Level ◽  
Message Content ◽  
Data Set ◽  
Sina Weibo ◽  
Content Type ◽  
User Influence

Purpose With the development and application of mobile internet access, social media represented by Weibo, WeChat, etc. has become the main channel for information release and sharing. High-impact users in social networks are key factors stimulating the large-scale propagation of information within social networks. User influence is usually related to the user’s attention rate, activity level, and message content. The paper aims to discuss these issues. Design/methodology/approach In this paper, the authors focused on Sina Weibo users, centered on users’ behavior and interactive information, and formulated a weighted interactive information network model, then present a novel computational model for Weibo user influence, which combined multiple indexes such as the user’s attention rate, activity level, and message content influence, etc., the model incorporated the time dimension, through the calculation of users’ attribute influence and interactive influence, to comprehensively measure the user influence of Sina Weibo users. Findings Compared with other models, the model reflected the dynamics and timeliness of the user influence in a more accurate way. Extensive experiments are conducted on the real-world data set, and the results validate the performance of the approach, and demonstrate the effectiveness of the dynamics and timeliness. Due to the similarity in platform architecture and user behavior between Sina Weibo and Twitter, the calculation model is also applicable to Twitter. Originality/value This paper presents a novel computational model for Weibo user influence, which combined multiple indexes such as the user’s attention rate, activity level, and message content influence, etc.

scholarly journals Possibilities of Psychological Intervention on Social Networks

2018 ◽  
Vol 8 (3) ◽  
pp. 35-49 ◽  
Author(s):  
Marek Madro
Keyword(s):  
Social Networks ◽  
Domestic Violence ◽  
Psychological Intervention ◽  
Personal Contact ◽  
Online Groups ◽  
Field Worker ◽  
Self Help ◽  
Group Members ◽  
Online Disinhibition ◽  
Self Help Groups

AbstractIntroduction: Nowadays we are looking for help and answers to our questions more and more often on the Internet. People use social networks to search for communities or groups whose members experience similar difficulties. These are often online groups that focus on psychological problems, domestic violence, etc. Members receive instant feedback and at the same time, due to the online disinhibition effect, they do not feel the fear, shame or worries they would feel in personal contact (Griffiths, 2005). The content of such self-help groups is not always helpful, but may rather induce pathological behaviour. However, the group administrator can influence the atmosphere in the group and its content itself (Niwa & Mandrusiak, 2012).Purpose: The purpose of this research was to find a space to perform professional psychological interventions inside online self-help groups on social networks. The concept of a field worker was used in this research. The field worker offers helping services to clients in an environment natural to them and where the worker can provide the client with emergency help during the crisis and prevent other clients from offering risk advices (Ambrózová, Vitálošová, & Labáth, 2006).Methods: We have conducted qualitative research using the method of content-frequency analysis. The sample for this study consisted of 10 closed online self-help groups focusing on topics such as depression, anxiety disorder, domestic violence, self-injurious and suicidal thoughts and tendencies, etc. For the purpose of this research we created an online group moderated by professionals, focusing on similar topics of mental disorders.Conclusions: The research results indicated that group members exchanged useful information (35.43%), described their current difficulties they were experiencing (32.33%), shared their own experiences (10.53%), and also published information on what had helped them manage the difficult feelings and situations they had been experiencing (6.39%). However, we also identified risky statements and threatening recommendations in posts and comments. Based on the results, we outlined the possibilities of online field worker interventions and described techniques of interventions that the professional can use for the benefit of group members.

scholarly journals A Study of Rumor Detection based on Social Network Topic Models Relationship

2020 ◽  
Author(s):  
Diogo Nolasco ◽  
Jonice Oliveira
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Local Community ◽  
Topic Model ◽  
Fake News ◽  
Detection Problem ◽  
Model Method ◽  
Show Evidence ◽  
Rumor Detection ◽  
Scientific Topic

The rumor detection problem on social networks has attracted considerable attention in recent years with the rise of concerns about fake news and disinformation. Most previous works focused on detecting rumors by individual messages, classifying whether a post or blog entry is considered a rumor or not. This paper proposes a method for rumor detection on topic-level that identifies whether a social topic related to a scientific topic is a rumor. We propose the use of a topic model method on social and scientific domains and correlate the topics found to detect the most prone to be rumors. Results applied in the Zika epidemic scenario show evidence that the least correlated topics contain a mix of rumors and local community discussions.

scholarly journals Optimizing community detection in social networks using antlion and K-median

2019 ◽  
Vol 8 (4) ◽  
Author(s):  
Amany A. Naem ◽  
Neveen I. Ghali
Keyword(s):  
Social Networks ◽  
Objective Function ◽  
Community Detection ◽  
Optimization Problem ◽  
Real Life ◽  
Optimization Methods ◽  
Population Based ◽  
Detection Problem ◽  
Network Communities ◽  
Antlion Optimization

Antlion Optimization (ALO) is one of the latest population based optimization methods that proved its good performance in a variety of applications. The ALO algorithm copies the hunting mechanism of antlions to ants in nature. Community detection in social networks is conclusive to understanding the concepts of the networks. Identifying network communities can be viewed as a problem of clustering a set of nodes into communities. k-median clustering is one of the popular techniques that has been applied in clustering. The problem of clustering network can be formalized as an optimization problem where a qualitatively objective function that captures the intuition of a cluster as a set of nodes with better in ternal connectivity than external connectivity is selected to be optimized. In this paper, a mixture antlion optimization and k-median for solving the community detection problem is proposed and named as K-median Modularity ALO. Experimental results which are applied on real life networks show the ability of the mixture antlion optimization and k-median to detect successfully an optimized community structure based on putting the modularity as an objective function.

scholarly journals Study of Construction of Network English Teaching Platform Based on Multimedia

2017 ◽  
Vol 12 (02) ◽  
pp. 78
Author(s):  
Qian Zhang
Keyword(s):  
Social Networks ◽  
Rapid Development ◽  
Multimedia Technology ◽  
Important Research ◽  
College English ◽  
English Teaching ◽  
Teaching Platform ◽  
Interactive Network ◽  
Research Goal ◽  
Listening And Speaking

In order to adapt to the needs of the rapid development of social networks, how to effectively improve college students’ English comprehensive application ability, and rapidly improve listening and speaking skills has become an important research goal of college English teaching. This paper describes the main problems to be solved, and makes full use of the network and multimedia technology to build an open, interactive network English teaching platform. The platform provides students with abundant videos, images, voices, texts and other resources, so that the students can get help from teachers and other partners to improve their English ability.

Social Media as a Tool, and Tools Offered by Social Media, to Teachers and Researchers

2017 ◽  
pp. 66-80
Author(s):  
Jose-Luis Poza-Lujan ◽  
Ángeles Calduch-Losa
Keyword(s):  
Social Networks ◽  
Social Media ◽  
New Media ◽  
Point Of View ◽  
Message Content ◽  
Research Activity ◽  
Clear Vision ◽  
Personal Brand ◽  
The Social ◽  
Evaluation Mechanism

The present chapter provides a clear vision for the social networks environment from the self-promotion point of view. Chapter focuses on organizing tools, audience, and type of publications. Tools are organized to contextualize their use and to give a proper understanding of the relevant contents that can be published. Audience is presented according to the relations and interests with the teacher and researcher. Simultaneously, chapter gives a vision of the privacy scope or the publications, and provides an evaluation mechanism to distinguish the most convenient area of publication depending of the message content. Following submission of these analyses, chapter focuses on the teacher and research activity and how to promote these activities through social networks. The chapter ends with a set of suggestions to make a strategic use of new media with the goal of promoting efficiently personal brand as a teacher and researcher.

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