scholarly journals Analysis of sentiments conveyed through Twitter concerning COVID-19

2021 ◽  
Vol 119 ◽  
pp. 07003
Author(s):  
Mohamed Chiny ◽  
Marouane Chihab ◽  
Omar Bencharef ◽  
Younes Chihab
Keyword(s):  
Social Network ◽  
Sentiment Analysis ◽  
High Frequency ◽  
Analysis Approach ◽  
Economic Aspects ◽  
The Social

Due to the social and economic fallout from the COVID-19 pandemic, we sought to gauge the attitudes of social network users, in this case, Twitter, towards the topic using a sentiment analysis approach. We collected 178,683 tweets using the Twitter API based on queries for the high-frequency hashtag #covid19. After the preprocessing step, we classified them in a binary way (positive and negative) and according to their intensity (valence) using the VADER model and then the NRCLex dictionary, which allows us to classify feelings according to their affective class. The results suggest that overall, the feelings detected through the tweets are positive. In addition, users seem to be interestedin the pandemic as a trend rather than as a topic related to other social or economic aspects.

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.

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.

scholarly journals Assorted Sentiment Model for Publically Available Page of Facebook

2020 ◽  
Vol 9 (3) ◽  
pp. 1160-1167
Keyword(s):  
Social Network ◽  
Sentiment Analysis ◽  
Business Strategy ◽  
English Language ◽  
Learning Algorithm ◽  
Indian Languages ◽  
Analysis Model ◽  
Indian Language ◽  
The Social ◽  
Bayes Algorithm

ecommerce industries expose public page in the social network site (Facebook, twitter etc) for the intention of improving of business strategy. They extract public mood about the social network page in the forms of total likes, the total share of the page and sentiment of all comments to the social network page similar way celebrities expose public page in the social network sites for the intention of improving its fame. We have developed an assorted model for publicly available page of Facebook. This assorted model is the combination of data extractor model, language convertor and cleaned model, and sentiment analyzer model. Our data extractor model extract comments on all the posts of publicly expose Facebook page in the less span of time. Language convertor and cleaned model would work for conversion of text written in different Indian language to the English language and after that English written text would be cleaned through cleaned model. Language convertor is made after implementing CILTEL model. CILTEL model converts comments written in the Indian languages in the English language. Cleaning model will clean all the comments of all the posts on the Facebook page. Finally, sentiment extraction model will extract sentiments of all the comments of the Facebook page. We have implemented classification using three machine learning algorithm, namely naïve bayes algorithm, perceptron algorithm and rocchio algorithm for checking the performance of our sentiment analysis model. Our assorted sentiment analysis model is beneficial to users like marketing industry, election parties and celebrities

Political journalists’ corporate and personal identities on Twitter profile pages: A comparative analysis in four Westminster democracies

2017 ◽  
Vol 20 (4) ◽  
pp. 1488-1505 ◽  
Author(s):  
Folker Hanusch
Keyword(s):  
Social Media ◽  
Social Network ◽  
Comparative Analysis ◽  
Personal Information ◽  
The Self ◽  
Economic Aspects ◽  
The United Kingdom ◽  
The Social ◽  
Political Journalists ◽  
Media Systems

The practice for journalists to present an identity and brand the self on social media has become common across many newsrooms, yet its practice is still poorly understood. Focusing on journalists’ self-representations on the social network site Twitter, this study aims to address the lack of empirical understanding through an analysis of the identities which political journalists present on their Twitter profile pages. A total of 679 accounts of parliamentary press gallery journalists in Australia, Canada, New Zealand and the United Kingdom were analyzed, with a focus on various textual and visual pieces of professional and personal information. The article develops scales of corporate and personal identity, finding that UK and Canadian journalists most strongly differentiate between personal and corporate identities. Differences across countries are linked to political and economic aspects of the respective media systems.

Research and Prototype Implementation of Network Group Sentiment Analysis Based on Topic

2014 ◽  
Vol 1042 ◽  
pp. 218-223
Author(s):  
Ya Hao He ◽  
Ya Ru Yang ◽  
Yu Zhong Qian ◽  
Jing Li
Keyword(s):  
Data Mining ◽  
Social Network ◽  
Sentiment Analysis ◽  
Group Structure ◽  
Complex Relationship ◽  
Mining Technology ◽  
Prototype Implementation ◽  
The Social

In the era of Web2.0, people in the social network make up a complex relationship called group by communicating with others, such as forward or comment. Such networks are typically abundant with valuable information which can be mined. We use data mining technology to analyze the network group structure based on different topics, divide the network group into multiple sub-communities, analyze sentimenttendency of different communities, views and frequentpatterns, and present the overall characteristics of whole group visually to the users to help them make decisions.

scholarly journals Russian Diminutives on the Social Network Instagram

2021 ◽  
Vol 12 (4) ◽  
pp. 981-995
Author(s):  
Armine A. Grigoryan ◽  
Elena N. Strelchuk
Keyword(s):  
Social Network ◽  
High Frequency ◽  
World View ◽  
Virtual Space ◽  
The Internet ◽  
Formal Expression ◽  
The Social ◽  
The World ◽  
Occasional Occurrence ◽  
Positive Evaluation

The article is devoted to the peculiarities of communication on the Russian-speaking segment of the social net Instagram. The aim of the article makes the analysis of diminutives - the words with diminutive-hypocoristic suffixes. In course of the study, over 250 users pages of Instagram were analyzed, and the most high-frequency lexemes were chosen. The derivational analysis was carried out to sort out the groups of relevant suffixes, and such a phenomenon as the synonymy was revealed. As is proved, despite different formal expression, all suffixes of diminutives bear diminutive-hypocoristic (or just hypocoristic) meaning which helps express subjective positive evaluation in respect to the environment, and demonstrate emotions (also positive) in course of communication. As is marked, the use of diminutives on the social net is not an occasional occurrence, its one of the significant exponents of the world view of the Russian-speaking people. The demand of language bearers for the diminutives witnesses of their high linguistic potential allowing the forms to create aesthetical communication over the Internet virtual space.

scholarly journals The Measurement of Demographic Temperature Using the Sentiment Analysis of Data from the Social Network VKontakte

Mathematics ◽  
2021 ◽  
Vol 9 (9) ◽  
pp. 987
Author(s):  
Irina Evgenievna Kalabikhina ◽  
Evgeniy Petrovich Banin ◽  
Imiliya Abduselimovna Abduselimova ◽  
German Andreevich Klimenko ◽  
Anton Vasilyevich Kolotusha
Keyword(s):  
Social Networks ◽  
Public Opinion ◽  
Social Network ◽  
Sentiment Analysis ◽  
Russian Language ◽  
Temperature Ratio ◽  
Additional Result ◽  
Demographic Groups ◽  
The Social ◽  
Negative Comments

Social networks have a huge potential for the reflection of public opinion, values, and attitudes. In this study, the presented approach can allow to continuously measure how cold “the demographic temperature” is based on data taken from the Russian social network VKontakte. This is the first attempt to analyze the sentiment of Russian-language comments on social networks to determine the demographic temperature (ratio of positive and negative comments) in certain socio-demographic groups of social network users. The authors use generated data from the comments to posts from 314 pro-natalist groups (with child-born reproductive attitudes) and eight anti-natalist groups (with child-free reproductive attitudes) on the demographic topic, which have 9 million of users from all over Russia. The algorithm of the sentiment analysis for demographic tasks is presented in the article. In particularly, it was found that comments under posts are more suitable for analyzing the sentiment of statements than the texts of posts. Using the available data in two types of groups since 2014, we find an asynchronous structural shift in comments of the corpuses of pro-natalist and anti-natalist thematic groups. Interpretations of the evidences are offered in the discussion part of the article. An additional result of our work is two open Russian-language datasets of comments on social networks.

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

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