Data Analysis in Social Networks Based on Similarity Measurements on Multi-attribute Trajectories

2019 ◽  
pp. 518-526
Author(s):  
K. Monica Rachel ◽  
D. C. Joy Winnie Wise ◽  
K. Raja Sundari ◽  
N. Raja Priya
Keyword(s):  
Social Networks ◽  
Data Analysis

Ricerca preliminare sulla valutazione Italiana dell'Internet Disorder Scale – Short Form (IDS9-SF)

2019 ◽  
Author(s):  
Paolo Soraci
Keyword(s):  
Social Networks ◽  
Factor Analysis ◽  
Data Analysis ◽  
Concurrent Validity ◽  
Short Form ◽  
Analysis Techniques ◽  
Validity Criterion ◽  
Preliminary Research ◽  
Nomological Validity ◽  
Italian Territory

The purpose of this study is to create a new tool capable of diagnosing the severity of internet addiction (IA) and is based on the nine IGD criteria. These same criteria were suggested by the APA in the last edition of the DSM-51. A sample was recruited with a method of convenience and 300+ participants were recruited through different forums and social networks. The construct validity of the IDS9SF test was achieved through factor analysis and nomological validity. The concurrent validity, criterion and reliability of the test itself have been thoroughly investigated through the most common and consolidated data analysis techniques, confirming that the same test has sufficient psychometric properties to be used also in the Italian territory. Furthermore it is necessary to remember that this preliminary research is only valid in the field of data and statistics with all the limitations of the case and cannot be used for a real clinical evaluation.

Architecture of a distributed system for processing heterogeneous data from social networks

2020 ◽  
Vol 4 ◽  
pp. 97-100
Author(s):  
A.P. Pronichev ◽  
Keyword(s):  
Social Networks ◽  
Data Analysis ◽  
Distributed System ◽  
Heterogeneous Data ◽  
Analysis Process ◽  
Support Costs

The article discusses the architecture of a system for collecting and analyzing heterogeneous data from social networks. This architecture is a distributed system of subsystem modules, each of which is responsible for a separate task. The system also allows you to use external systems for data analysis, providing the necessary interface abstraction for connection. This allows for more flexible customization of the data analysis process and reduces development, implementation and support costs.

scholarly journals The Mistakes of a Public Communication in the Ebola Crisis in Spain

2017 ◽  
Vol 11 (2) ◽  
pp. 83
Author(s):  
Rafael Barberá González ◽  
Victoria Cuesta
Keyword(s):  
Social Networks ◽  
Data Analysis ◽  
Ebola Virus ◽  
Public Information ◽  
Hemorrhagic Fever ◽  
Public Communication ◽  
Good Resolution ◽  
The Public ◽  
The Media ◽  
The Impact

This work analyzes the impact of the outbreak of hemorrhagic fever caused by the Ebola virus in Spain in the field of communication. The communication of such a crisis entails an interaction of information between individuals and institutions. Accuracy in the messages that are disseminated is key to the good resolution of the crisis. In this case of the Ebola crisis the impact in the Spanish media was very remarkable not only of the evolution of the crisis but also of the public information that were being made known by the authorities. The errors committed in this public communication, especially in the first institutional appearance, will be analyzed and possible solutions will be provided for future crises. In addition, the information behavior that was given in social networks by the authorities will be analyzed. To perform this work, bibliographical sources, data analysis and the media have been used.

Genetic Algorithm Applied in the Social Network Data Analysis

2013 ◽  
Vol 427-429 ◽  
pp. 2188-2191
Author(s):  
Lei Liu ◽  
Quan Bao Gao
Keyword(s):  
Genetic Algorithm ◽  
Social Networks ◽  
Social Network ◽  
Data Analysis ◽  
Rapid Development ◽  
Virtual Community ◽  
Social Network Data ◽  
Starting Point ◽  
The Social ◽  
Optimal Data Analysis

The rapid development of network and information technology makes the network become the indispensable part in people's life. Network design uses email as a starting point, instead of actual letters. Then Happy Nets, BBS etc. are evolved from it, with virtual as their major feature. In the process of social networks evolution, the personal image transformed from the actual into the virtual one. All this has contributed to the birth of the social network, which then makes the contacts among people presenting the feature of network expansion and cost reduction. The popular social network nowadays is considered to be social plus network, namely, through the network, as a carrier, people are connected to form a virtual community with certain characteristics. Based on the genetic algorithm and genetic coding technology, the article is designed to make the optimal data analysis and create a optimistic cyber environment in the process of the social networks explosive development.

SAE: Toward Efficient Cloud Data Analysis Service for Large-Scale Social Networks

2017 ◽  
Vol 5 (3) ◽  
pp. 563-575 ◽  
Author(s):  
Yu Zhang ◽  
Xiaofei Liao ◽  
Hai Jin ◽  
Guang Tan
Keyword(s):  
Social Networks ◽  
Data Analysis ◽  
Large Scale ◽  
Cloud Data

scholarly journals Stance Taking in Social Media: the Analysis of the Comments About Us Presidential Candidates on Facebook and Twitter

Verbum ◽  
2018 ◽  
Vol 9 ◽  
pp. 21-30
Author(s):  
Roma Kriaučiūnienė ◽  
Jefferey La Roux ◽  
Miglė Lauciūtė
Keyword(s):  
Social Networks ◽  
Data Analysis ◽  
Empirical Data ◽  
Presidential Election ◽  
The United States ◽  
Online Environment ◽  
Presidential Candidates ◽  
Du Bois ◽  
Empirical Data Analysis ◽  
The Many

[full article and abstract in English] The subject of the paper is the analysis of the expression of stance taking in an online environment, mainly in the comments of users of social networks such as Facebook and Twitter about the presidential candidates of the American Presidential Election in 2016. The empirical data analysis was carried out following the ideas of J. W. Du Bois (2007), D. Barton & C. Lee (2013) and R. Englebretson (2007) on stance taking and J. W. Du Bois’ (2007) model of stance triangle, i.e. grouping instances of stance-taking into one of these groups: evaluation, affect or epistemicity, which served as the main framework of this study. The work of linguists D. Barton & C. Lee (2013) on the expression of stance-taking in an online environment were also taken into consideration. Having in mind the fact that stance identification is a challenging task , i.e. it could be implicitly as well as explicitly expressed and that it should be inferred from different modes of its expression and interpreted with reference to many contextual and intertextual factors, in the current analysis the authors focused on interpretation of linguistic as well as other multimodal means of the expression of stance that were used by users of social networks in their writing spaces on the topic of the Presidential Election in the United States in 2016. It should also be mentioned that the analysis presented in this article offers only one of the many possible interpretations of the data. Moreover, the current paper concentrates mainly on the presentation of the empirical data of the expression of affective stance. However, it should be indicated that in some cases stance types overlap, i.e. one instance could be treated as both taking an affective and an evaluative stance, as judgements and evaluation (i.e. evaluative stance) are often based on feelings (i.e. affective stance). The main source of the empirical data were the instances of stance taking taken from comments found on Donald Trump’s and Hillary Clinton’s verified Facebook and Twitter pages during their presidential campaigns in 2016. All in all, 147 examples of posts and comments from the social networks Facebook and Twitter were collected: 72 comments incorporating stance taking on Donald Trump‘s posts, and 75 comments including stance taking on Hillary Clinton‘s posts. The results of the empirical data analysis showed that the affective stance was expressed by linguistic as well as multimodal means.

scholarly journals The analysis of factors that effect business development and income of MSMEs in Denpasar city

2019 ◽  
Vol 6 (4) ◽  
pp. 118-126 ◽  
Author(s):  
I.B. Hendra Prawira D. ◽  
Heny Urmila Dewi
Keyword(s):  
Social Capital ◽  
Social Networks ◽  
Data Analysis ◽  
Working Hours ◽  
Business Development ◽  
Three Dimensions ◽  
Business Sector ◽  
Analysis Technique ◽  
Capital Ownership ◽  
The City

The population in this study were all MSMEs players in the city of Denpasar, amounting to 30,840 MSMEs and the number of samples used as many as 100 MSME actors with a method of determining stratified proportional sampling. The data analysis technique used is path analysis. The results of the analysis show that: 1) capital, labor, and social capital have a positive and significant effect on the development of MSMEs in Denpasar City. This means that the availability of capital, the working hours of MSME actors and the application of the three dimensions of social capital namely trust, social norms, and social networks are very influential on the development of the MSME business sector. 2) Capital, labor, social capital, and business development have a positive and significant effect on the income of SMEs in Denpasar City. This means that capital ownership, labor, social capital and the development of MSMEs will have a positive and significant impact on increasing the income of MSME players. 3) Business development is a variable that mediates the influence of capital, labor and social capital on the income of SMEs in Denpasar City.

scholarly journals Conceptual usage model of big data generated by social media

2020 ◽  
Vol 10 (2) ◽  
Author(s):  
Jolanta Sabaitytė ◽  
Roberta Karpovičiūtė
Keyword(s):  
Social Networks ◽  
Social Media ◽  
Big Data ◽  
Data Analysis ◽  
Conceptual Model ◽  
Decision Support Tool ◽  
Virtual Space ◽  
Management Tools ◽  
Support Tool ◽  
Customer Profiles

The digital revolution and the communication platforms provided by the Web 2.0 virtual space era, such as social media, social networks, other tools and channels, create new opportunities for better marketing decisions based on user-generated data analysis. Every day customers of social media and other virtual tools are creating huge amounts of their actions-caused data, and businesses lack management tools supporting this process, which could create knowledge in the areas of deeper cognitive customer profiles and preferences. The growing number of social media users indicates the popularity of these communication tools among the information society, but science today lacks a deeper knowledge of social media-generated data and other algorithms for this kind of data usage. Therefore, the purpose of the article can be defined as the development of a conceptual model of big data generated by social media usage in business. The formation of the conceptual model is based on the analysis of big data assumptions and application possibilities, social media classification peculiarities and different channel specifics, identification of big data analysis methods and analysis of big data applications generated by social media. The conceptual model creates preconditions for deeper knowledge of user-generated big data in nowadays’ widely used communication platforms, as well as creation of the decision support tool for marketing specialists in order to use big data from social media in deeper cognitive customer profiles and preferences. The methods employed in this research are literature and other references analysis, synthesis and logical analysis of information, comparison of information, systemisation and visualisation.   Keywords: Big data, data mining, social media, social networks, internet marketing.

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