scholarly journals Sentiment Analysis on Social Network

2021 ◽  
Vol 10 (2) ◽  
pp. 845-853
Keyword(s):  
Social Network ◽  
Sentiment Analysis ◽  
Social Connectedness ◽  
Social Web ◽  
Online Networks ◽  
The Social ◽  
Informal Communities ◽  
Travel Industry ◽  
The Web

As the Web quickly advances, Web clients are developing with it. In a time of social connectedness, individuals are turning out to be increasingly more excited about associating, sharing, and teaming up through informal communities, online networks, sites, Wikis, and other online communitarian media. Lately, this aggregate insight has spread on various zones, with specific spotlight on fields identified with regular daily existence, for example, business, the travel industry, instruction, and wellbeing, making the size of the Social Web extend exponentially

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.

Sentiment Analysis of Social Media as Tool to Improve Customer Retention

2017 ◽  
pp. 635-648
Author(s):  
Wafaa A. Al-Rabayah ◽  
Ahmad Al-Zyoud
Keyword(s):  
Social Media ◽  
Social Network ◽  
Literature Review ◽  
Competitive Advantage ◽  
Sentiment Analysis ◽  
Customer Retention ◽  
Unstructured Data ◽  
Amount Of Information ◽  
Business Applications ◽  
The Web

Sentiment analysis is a process of determining the polarity (i.e. positive, negative or neutral) of a given text. The extremely increased amount of information available on the web, especially social media, create a challenge to be retrieved and analyzed on time, timely analyzed of unstructured data provide businesses a competitive advantage by better understanding their customers' needs and preferences. This literature review will cover a number of studies about sentiment analysis and finds the connection between sentiment analysis of social network content and customers retention; we will focus on sentiment analysis and discuss concepts related to this field, most important relevant studies and its results, its methods of applications, where it can be applied and its business applications, finally, we will discuss how can sentiment analysis improve the customer retention based on retrieved data.

Sentiment Analysis of Social Media as Tool to Improve Customer Retention

2017 ◽  
pp. 207-223
Author(s):  
Wafaa A. Al-Rabayah ◽  
Ahmad Al-Zyoud
Keyword(s):  
Social Media ◽  
Social Network ◽  
Literature Review ◽  
Competitive Advantage ◽  
Sentiment Analysis ◽  
Customer Retention ◽  
Unstructured Data ◽  
Amount Of Information ◽  
Business Applications ◽  
The Web

Sentiment analysis is a process of determining the polarity (i.e. positive, negative or neutral) of a given text. The extremely increased amount of information available on the web, especially social media, create a challenge to be retrieved and analyzed on time, timely analyzed of unstructured data provide businesses a competitive advantage by better understanding their customers' needs and preferences. This literature review will cover a number of studies about sentiment analysis and finds the connection between sentiment analysis of social network content and customers retention; we will focus on sentiment analysis and discuss concepts related to this field, most important relevant studies and its results, its methods of applications, where it can be applied and its business applications, finally, we will discuss how can sentiment analysis improve the customer retention based on retrieved data.

Collaborative Finance and Its Hurdles to Overcome

2020 ◽  
pp. 239-262
Author(s):  
Elisabet Ruiz-Dotras ◽  
Krystyna Mitręga-Niestrój
Keyword(s):  
Social Network ◽  
Social Interaction ◽  
Financial Literacy ◽  
Financial Services ◽  
Peer To Peer ◽  
Online Networks ◽  
The Social ◽  
Finance Development ◽  
Personal Trust ◽  
Financial Issues

Using survey data from an online Spanish university, real and perceived financial literacy levels, social interactions and personal trust with the social network are measured as key elements for collaborative finance development. This is the first study regarding the factors that may affect the use of collaborative finance. Results show levels of financial literacy are quiet low as in prior studies and individuals consider that the bank manager, friends, and parents can manage financial issues better than them, with the last two peers being those who most trust to discuss financial issues. The findings also provide information about how little individuals trust online networks when it comes to financial matters. Besides, respondents interact moderately with their social network missing the benefits of peer-to-peer learning. Overall, lack of financial literacy, low social interaction, and personal trust may be affecting the short use of collaborative financial services.

Depressive Person Detection using Social Asian Elephants' (SAE) Algorithm over Twitter Posts

2019 ◽  
Vol 9 (4) ◽  
pp. 37-51
Author(s):  
Hadj Ahmed Bouarara
Keyword(s):  
Data Mining ◽  
Social Network ◽  
Decision Tree ◽  
Social Life ◽  
Naive Bayes ◽  
Data Sources ◽  
Asian Elephants ◽  
Person Detection ◽  
The Social ◽  
The Web

With the advent of the web and the explosion of data sources such as opinion sites, blogs and microblogs appeared the need to analyze millions of posts, tweets or opinions in order to find out what thinks the net surfers. The idea was to produce a new algorithm inspired by the social life of Asian elephants to detect a person in depressive situation through the analysis of twitter social network. The proposal algorithm gives better performance compared to data mining and bioinspired techniques such as naive Bayes, decision tree, heart lungs algorithm, social cockroach's algorithm.

Social Network Mining from the Web

2011 ◽  
pp. 149-175 ◽  
Author(s):  
Yutaka Matsuo ◽  
Junichiro Mori ◽  
Mitsuru Ishizuka
Keyword(s):  
Social Network ◽  
Search Engine ◽  
Relevant Information ◽  
Web Content ◽  
Message Boards ◽  
Network Information ◽  
Network Mining ◽  
Social Network Mining ◽  
The Social ◽  
The Web

This chapter describes social network mining from the Web. Since the end of the 1990s, several attempts have been made to mine social network information from e-mail messages, message boards, Web linkage structure, and Web content. In this chapter, we specifically examine the social network extraction from the Web using a search engine. The Web is a huge source of information about relations among persons. Therefore, we can build a social network by merging the information distributed on the Web. The growth of information on the Web, in addition to the development of a search engine, opens new possibilities to process the vast amounts of relevant information and mine important structures and knowledge.

The Alt-social Network of Natalie Bookchin’s Testament

2016 ◽  
Vol 18 (5) ◽  
pp. 459-477
Author(s):  
Sarah Whitcomb Laiola
Keyword(s):  
Data Mining ◽  
Social Networks ◽  
Social Media ◽  
Social Network ◽  
Online Social Networks ◽  
Social Web ◽  
User Interactions ◽  
Media Criticism ◽  
Direct Translation ◽  
The Social

This article addresses issues of user precarity and vulnerability in online social networks. As social media criticism by Jose van Dijck, Felix Stalder, and Geert Lovink describes, the social web is a predatory system that exploits users’ desires for connection. Although accurate, this critical description casts the social web as a zone where users are always already disempowered, so fails to imagine possibilities for users beyond this paradigm. This article examines Natalie Bookchin’s composite video series, Testament, as it mobilizes an alt-(ernative) social network of vernacular video on YouTube. In the first place, the alt-social network works as an iteration of “tactical media” to critically reimagine empowered user-to-user interactions on the social web. In the second place, it obfuscates YouTube’s data-mining functionality, so allows users to socialize online in a way that evades their direct translation into data and the exploitation of their social labor.

scholarly journals Excava(c)tion in Vignale. Archaeology on stage, archaeology on the Web

2017 ◽  
Vol 3 ◽  
pp. 97 ◽  
Author(s):  
Stefano Costa ◽  
Francesco Ripanti
Keyword(s):  
Local Community ◽  
Integrated Approach ◽  
Common Interest ◽  
Social Web ◽  
Archaeological Excavation ◽  
The Public ◽  
The Social ◽  
Guided Tours ◽  
The Web ◽  
Potential Integration

As an orchestra or a rock star, archaeologists have their audience too. This paper wants to highlight an integrated approach between fieldwork, its account and its dissemination to the public in different ways, including social media. This potential integration has come to life in the 2011 excavation of the Roman mansio of Vignale (Italy) and it has been named “Excava(c)tion”. It doesn’t mean a new way of digging but another way of approaching the excavation, an approach integrated toward and with the public, both on site and on the social Web. “Excava(c)tion” conceives the site as a stage and digging as a performance, through a continuous dialogue between archaeologists and the public. Archaeologists share their work in the form of guided tours (live, theatrical-like performances), communicative diaries and videos (edited, motion-picture performances) and on a blog (www.uominiecoseavignale.it). They receive back comments and oral accounts from the local community about the main themes of common interest. “Excava(c)tion” means engagement both of archaeologists and the public in the pursuit of a global multivocality during archaeological excavation.

scholarly journals Trash Stream: Social Conditioning of Criminalization

2021 ◽  
Vol 16 (6) ◽  
pp. 202-210
Author(s):  
Yu. V. Gracheva ◽  
S. V. Malikov
Keyword(s):  
Social Network ◽  
Criminal Law ◽  
Deviant Behavior ◽  
Criminal Liability ◽  
Digital Technologies ◽  
The Internet ◽  
Social Conditioning ◽  
The Social ◽  
Live Broadcast ◽  
The Web

The social network as one of the digital technologies has not only creates a platform for communications, especially relevant during a pandemic, but also provokes the emergence of various types of deviant behavior, primarily due to the fact that many communicate on the Internet under fictitious names; it liberates a person, creates a feeling of impunity, control over the situation, etc. Recently, trash streams have become popular on the Web, but not funny and silly, but associated with violence, insult, humiliation of human dignity, causing a feeling of disgust and contrary to public morality. In December 2020, during such a live broadcast, another victim died, which launched a process in society to discuss the need to introduce criminal liability for such acts. The paper assesses the draft criminal law, as well as initiatives to supplement the list of aggravating circumstances and some corpus delicti with an appropriate qualifying feature, and formulates the author’s draft criminal law on responsibility for organizing, conducting, facilitating and participating in direct air in trash streams.

scholarly journals Database “Childfree (antinatalist) communities in the social network VKontakte”

2021 ◽  
Vol 5 (2) ◽  
pp. 92-96
Author(s):  
Irina E. Kalabikhina ◽  
Evgeny P. Banin
Keyword(s):  
Social Network ◽  
Sentiment Analysis ◽  
Thematic Analysis ◽  
Latent Dirichlet Allocation ◽  
Absolute Amount ◽  
Graph Structure ◽  
Unique Identifier ◽  
Text Data ◽  
Structure Of Communities ◽  
The Social

The database contains an upload of text comments in Russian from the social network VKontakte in .csv format (UTF-8 encoding). The comments are collected from communities, which discuss pregnancy, childhood, motherhood, paternity, etc. The upload contains comments under the posts with which the interaction took place. The absolute amount of likes is used as a criterion (comments are collected where the number of likes is greater than or equal to 5). The text data is processed (stemmization and lemmatization). The data are suitable for thematic analysis (e.g. LDA — Latent Dirichlet Allocation), sentiment analysis of statements, modelling the graph structure of communities (the link_comment variable contains a unique identifier of the post, link_author contains a unique user identifier), and forming a dictionary of demographic connotation in Russian. Sentiment analysis of statements enables measuring the dynamics of «demographic temperature» in antinatalist communities. The database is a supplement to the publication Kalabikhina IE, Banin EP (2020) Database «Pro-family (pronatalist) communities in the social network VKontakte». Population and Economics 4(3): 98–130. https://doi.org/10.3897/popecon.4.e60915.

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