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Social network analyzer on the example of Twitter
P. 020069-1–020069-3.
Khruslova D. V., Городецкая М. А.
Social networks are powerful sources of data due to their popularity. Twitter is one of the networks providing a lot of data. There is need to collect this data for future usage from linguistics to SMM and marketing. The report examines the existing software solutions and provides new ones. The study includes information about the software developed. Some future features are listed.
In book
AIP Publishing LLC, 2017.
Nazarova A., Malik M. S., Ignatov D. I. et al., Social Network Analysis and Mining 2024 Vol. 14 Article 228
Identifcation of threatening comments on social media platforms has recently gained attention. Prior approaches have addressed
this task in some low-resource languages but the interpretability of results was not studied. In addition, approaches in the English
language are minimal. To support explainable predictive inference, this research proposes an inherently explainable model for threat
comment identifcation on Twitter. The ...
Added: December 11, 2024
Malik M. S., Younas M. Z., Jamjoom M. M. et al., PeerJ Computer Science 2024 Vol. 10 Article e1859
Identification of infrastructure and human damage assessment tweets is beneficial to disaster management organizations as well as victims during a disaster. Most of the prior works focused on the detection of informative/situational tweets, and infrastructure damage, only one focused on human damage. This study presents a novel approach for detecting damage assessment tweets involving infrastructure ...
Added: February 16, 2024
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Web mining analyzes web content, its usage and structure. The users’ behavior, interaction and generated content analysis have vast applications such as market analysis, social issues examination and study of human behavior. Twitter is a widely used social network that provides short message facility to its users to generate their own content. There are a ...
Added: November 29, 2023
Molodchik M., Гагарин А. С., Елтышев Р. А., Российский журнал менеджмента 2023 Т. 21 № 1 С. 5–22
Goal: the paper evaluates the impact of a company’s digital image on its value. Methodology: the authors use panel data analysis applied to a large array of information on the news of the 25 largest US medias, the Google Trends web application and the Twitter social network for the period from 2017 to 2022 for ...
Added: November 28, 2023
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This paper discusses the interaction between social media and the Russian 2011- 2013 protests. First, it critically observes the existing analytical work on the role of social media in movements worldwide, situating the Russian experience within this context. Sec- ondly, it examines sporadic facts and presuppositions by mapping and analysing a large num- ber of ...
Added: April 12, 2023
Sosnin A., Balakina Y. V., Jucovscaia A., Ezikov Svyat 2023 Vol. 21 No. 1 P. 96–109
The article implements an integrated approach to examining the mobilization potential of Twitter, which incorporates an analysis of intentions stated by the authors of hashtags and messages. The study cited in the article proceeds from J. Austin and J. Searle’s approach who argued that any utterance is essentially preparedness to perform an action, and examines ...
Added: February 27, 2023
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The research results devoted to the construction and analysis of the stochastic nonlinear dynamic system of
equations that simulate the self-organization of Twitter into the critical state are presented. A nonlinear dynamic system links three dynamic variables. The first variable corresponds to the order parameter determined by the average size of avalanches of microposts (tweets, retweets). The second ...
Added: December 10, 2022
Stukal D., Sanovich S., Bonneau R. et al., American Political Science Review 2022 Vol. 116 No. 3 P. 843–857
There is abundant anecdotal evidence that nondemocratic regimes are harnessing new digital technologies known as social media bots to facilitate policy goals. However, few previous attempts have been made to systematically analyze the use of bots that are aimed at a domestic audience in autocratic regimes. We develop two alternative theoretical frameworks for predicting the ...
Added: November 14, 2022
Smetanin S., PeerJ Computer Science 2022 No. 8 Article e1039
The Russian language is still not as well resourced as English, especially in the field of sentiment analysis of Twitter content. Though several sentiment analysis datasets of tweets in Russia exist, they all are either automatically annotated or manually annotated by one annotator. Thus, there is no inter-annotator agreement, or annotation may be focused on ...
Added: June 29, 2022
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Added: December 1, 2021
Товкес М. Ю., Вестник Новосибирского государственного университета. Серия: Лингвистика и межкультурная коммуникация 2021 Т. 19 № 2 С. 118–132
The study focuses on issues related to gender stereotypes of the blog community based on bloggers’ individual reactions and their impact on the perception of female politicians. The sample comprises tweets of the Russian- and English-speaking segments of this microblog, selected by keywords (based on the researcher’s view on the component structure of the thematic ...
Added: September 25, 2021
Gabrielova E., Maksimenko O., Russian Journal of Linguistics 2021 Vol. 25 No. 1 P. 105–124
The current research answers the question how Twitter users express their evaluation of the topical social problem (explicitly or implicitly) and what linguistic means they use being restricted by the limited length of the message. The article explores how Twitter users socialize with each other and exchange ideas on social issues of great importance, express ...
Added: January 11, 2021
Akhremenko A. S., Ilya Filippov, Yureskul E., , in: 2020 International Conference on Engineering Management of Communication and Technology (EMCTECH), 20-22 October 2020, Vienna, Austria.: IEEE, 2020. P. 1–7.
In this paper we present the results of computational experiments based on a novel agent-based communication model of Twitter activity. The model was designed specifically for analyzing the dynamics of communication between competing ideological positions, which sets the model apart from existing modelling literature. The model incorporates network structures into an agent-based framework; the nodes ...
Added: December 13, 2020
Kharlamov A. A., Orekhov A., Bodrunova S. et al., Lecture Notes in Computer Science 2019 Vol. 11938 P. 18–31
Till today, classification of documents into negative, neutral, or positive remains a key task within the analysis of text tonality/sentiment. There are several methods for the automatic analysis of text sentiment. The method based on network models, the most linguistically sound, to our viewpoint, allows us take into account the syntagmatic connections of words. Also, ...
Added: October 29, 2020
Oldring A., Milekhina A., Brand A., Canadian Journal of Communication 2020 Vol. 45 No. 3 P. 387–409
Background Although early warning has been studied on Twitter, research focused on Canada is rare. British Columbia, Canada, is vulnerable to tsunamis, and warning systems are not ubiquitous. Establishing pre-event networks can contribute to understanding early warning dissemination potential in the province.
Analysis This study locates a 1,932 follower network for @NWS_NTWC, a Twitter handle for the U.S. ...
Added: October 28, 2020
Akhremenko A. S., Stukal D., Petrov A., Полис. Политические исследования 2020 № 2 С. 73–91
Social media can act as environments that accumulate and concentrate protest sentiment before it brings people to the streets. The social ties that connect people online are similar to their offline ties, and their structure can affect the diffusion of both the protest-related information and the protest itself. In addition, social media can serve as ...
Added: May 26, 2020
Balakina Y. V., Товкес М. Ю., Вестник Санкт-Петербургского университета. Язык и литература 2019 Т. 16 № 3 С. 381–399
The presented research is devoted to the issues related to the ambiguous attitude towards women's participation in politics. The relevance of the study is explained by underrepresentation of women in the decision-making sphere. The presidential elections in the United States (2016) and Russia (2018), where women were registered as candidates, served as a newsbreak for ...
Added: April 2, 2019
Balakina Y. V., Жуковская А., Вестник Пермского университета. Серия: Политология 2019 Т. 13 № 1 С. 47–58
The topicality of the research is explained by the growing popularity of social networks as a channel of political communication. Modern elements of intertextuality, such as hashtags, retweets, @ sign, ensure participation of a large number of users in the discussion of certain political topics, and allow to quickly track public's reaction to political events. ...
Added: February 6, 2019
Yampolsky S., Сазыкин А. М., Зайцев А. И., Вопросы оборонной техники. Серия 16: Технические средства противодействия терроризму 2018 № 123-124 С. 54–62
The article presents the sequence of activities of the military command and control bodies taking into consideration the use of the means of the information and analytical support. Article also describes the requirements in relation to the above mentioned means of support as well as specific terms of its structural composition. ...
Added: November 13, 2018
Dmitriev V., Dmitriev A., Discontinuity, Nonlinearity, and Complexity 2018 Vol. 7 No. 4 P. 403–411
The present paper is devoted to the investigation into the nonlinear dynamics of Twitter. A new model of Twitter as a thermodynamic non-equilibrium system is suggested. Dynamic variables of such system are represented by the variations of tweet/retweet number and instantaneous diversity between the densities of population on different levels around the equilibrium values. Regular ...
Added: October 26, 2018
Gromov V., Konev A., Neural Computing and Applications 2017 Vol. 28 No. 11 P. 3317–3322
The present paper outlines a novel approach to predict popularity of topics for social network Twitter; the method is designed to identify precociously the topics able to demonstrate “explosive” growth in popularity. First of all, the predictive clustering method ascertains real (not written in hash-tags!) topics of tweets and then predicts popularity rates for the ...
Added: September 27, 2018