Social Text Research Articles

Supervised Character Resemble Substitution Personality Adversarial Method

With the development of science and computer technology, social networks are changing our daily lives. However, this leads to new, often hidden dangers in areas such as cybersecurity. Of these, the most complex and harmful is the Advanced Persistent Threat attack (APT attack). The development of personality analysis and prediction technology provides the APT attack a good opportunity to infiltrate personality privacy. Malicious people can exploit existing personality classifiers to attack social texts and steal users’ personal information. Therefore, it is of high importance to hide personal privacy information in social texts. Based on the personality privacy protection technology of adversarial examples, we proposed a Supervised Character Resemble Substitution personality adversarial method (SCRS) in this paper, which hides personality information in social texts through adversarial examples to realize personality privacy protection. The adversarial examples should be capable of successfully disturbing the personality classifier while maintaining the original semantics without reducing human readability. Therefore, this paper proposes a measure index of “label contribution” to select the words that are important to the label. At the same time, in order to maintain higher readability, this paper uses character-level resemble substitution to generate adversarial examples. Experimental validation shows that our method is able to generate adversarial examples with good attack effect and high readability.

The neural machine translation models for the low-resource Kazakh-English language pair.

The development of the machine translation field was driven by people's need to communicate with each other globally by automatically translating words, sentences, and texts from one language into another. The neural machine translation approach has become one of the most significant in recent years. This approach requires large parallel corpora not available for low-resource languages, such as the Kazakh language, which makes it difficult to achieve the high performance of the neural machine translation models. This article explores the existing methods for dealing with low-resource languages by artificially increasing the size of the corpora and improving the performance of the Kazakh-English machine translation models. These methods are called forward translation, backward translation, and transfer learning. Then the Sequence-to-Sequence (recurrent neural network and bidirectional recurrent neural network) and Transformer neural machine translation architectures with their features and specifications are concerned for conducting experiments in training models on parallel corpora. The experimental part focuses on building translation models for the high-quality translation of formal social, political, and scientific texts with the synthetic parallel sentences from existing monolingual data in the Kazakh language using the forward translation approach and combining them with the parallel corpora parsed from the official government websites. The total corpora of 380,000 parallel Kazakh-English sentences are trained on the recurrent neural network, bidirectional recurrent neural network, and Transformer models of the OpenNMT framework. The quality of the trained model is evaluated with the BLEU, WER, and TER metrics. Moreover, the sample translations were also analyzed. The RNN and BRNN models showed a more precise translation than the Transformer model. The Byte-Pair Encoding tokenization technique showed better metrics scores and translation than the word tokenization technique. The Bidirectional recurrent neural network with the Byte-Pair Encoding technique showed the best performance with 0.49 BLEU, 0.51 WER, and 0.45 TER.

Ethics of Technology Practice: Beliefs and Behaviors of Certified Rehabilitation Counselors During the COVID-19 Pandemic.

The coronavirus (COVID-19) pandemic represented a critical moment for technology use within rehabilitation counseling. This study explored trends in the beliefs and behaviors of certified rehabilitation counselors (CRCs) regarding the ethical use of technology before and during the pandemic. Specifically, this study compared two groups of CRCs regarding the degree to which they engaged in 59 technology behaviors and whether they viewed each behavior to be ethical. Overall, group comparisons suggested an increased use of telephone, videoconferencing, and email to deliver counseling, assessment, and supervision services during the pandemic. Furthermore, supervision via videoconferencing and email in the pandemic were rated as more ethically appropriate than before the pandemic. As a general trend, synchronous modes of communication such as the telephone and video conferencing were rated as more ethically appropriate than asynchronous modes such as social networking and text messaging. Indicating a high degree of congruence between beliefs and behaviors, the technology practices viewed as most ethical were used the most often. Implications address the revisions to the Code of Professional Ethics for Rehabilitation Counselors regarding the ethical use of technology in rehabilitation counseling.

Social Network Text Sentiment Analysis Method Based on CNN-BiGRU in Big Data Environment

Aiming at the serious colloquialism of social network texts and the sparse semantic features, this article proposes a CNN-BiGRU-based sentiment analysis method for social network texts in the big data environment. First, the dependency syntax tree is introduced to represent the dependency relationship between words to construct the word vector to represent the text. Then, sentiment features with different granularity are extracted by multiple convolution kernels of different sizes in a convolution neural network (CNN). These sentiment features are input into bidirectional gated recurrent unit (BiGRU) network for analysis to obtain deeper sentiment features. Finally, a certain number of neurons are discarded by the Dropout method, and sentiment types are classified by the Sigmoid activation function. The Weibo_senti_100k Weibo data set is used to demonstrate the proposed method. The results show that if the Dropout value is set to 0.25 and the Adam optimizer is selected, the analysis performance is the best. The accuracy, precision, recall, and AUC are about 94.09%, 95.13%, 92.87%, and 0.953, respectively, which has certain application value.

Transgressive marginalities in youth pop culture: negotiating the challenges of the post-colony in contemporary Zimbabwe

In the last two decades, Zimbabwe has faced a series of intractable political and socio-economic crises, resulting in abject economic collapse, stratospheric levels of inflation and massive youth unemployment. The country’s youth have responded to these endless crises through creative artistic expression via music and satirical videos, which are often circulated on social media platforms. This cultural activism by Zimbabwean youth is indicative of the distinctive ways in which the intersections of media globalization and situated local conditions have animated new popular cultural forms by youth in Africa. This paper, harnesses Nancy Fraser’s (Fraser, N., 1990. Rethinking the public sphere: a contribution to the critique of actually existing democracy. Social Text (25-26), 56–80) concept of alternative public spheres and Mikhail Bakhtin’s (Bakhtin, M., 1984. Rabelais and his world. Translated by Helene Iswolsky. Bloomington, IN: Indiana University Press.) notion of the carnival to analyse young people’s satirical videos posted on social media as creative responses that are used to protest the lived realities of economically marginalized youths even as they articulate significant needs and aspirations of their own. The paper views and analyses social media as a platform that is used to criticise and lampoon post-colonial excesses by the ruling elite who wield political and economic power. Youth popular culture is explored as a platform on which urban youths have sought to highlight and to contest the politics of survival in contemporary Zimbabwe in some highly creative and innovative ways.

Идеологические смыслы социальной рекламы нового времени (на материале текстов, посвященных СВО)

The article analyzes the problem of linguistic originality of social advertising texts devoted to the topic of the special military operation (abbreviated as SVO) conducted by the Russian Federation in the territory of Ukraine. The research field also includes advertising texts concerning the events of the Great Patriotic War as a historical event closely related to the current military-political situation. The article aims to study the language and content of social advertising texts devoted to the SVO in order to identify the ideological implications contained in them. Research methods: basic principles of philosophy, sociology, media linguistics as well as the lexico-semantic and functional-stylistic methods. Results: the paper discusses different approaches to the concept of ‘ideology’ and presents it as socially, politically, and morally significant in the context of the Basic Law (Constitution) of the Russian Federation. Following an analysis of the results of globalization, digitalization, and mediatization in modern society, the conclusion is made about the negative consequences of the absence of formulated parameters of state ideology in the Basic Law. An analysis of the linguistic and content features of the texts, conducted through the prism of the problem of creating a new state ideology, showed the presence of a large ideological and educational potential in social advertising related to the SVO; the author comes to the conclusion about the lexical and polycode diversity of expression of historical and cultural ideological implications in the studied texts. In the conclusion of the article, it is stated that texts related to the SVO are directly involved in the process of search for the main values underlying the new Russian ideology.

Automatic Smart Crawling on Twitter for Weather Information in Indonesia

Although Twitter is a popular platform for social interaction analysis and text data mining, it faces challenges with geolocation automation. To address this problem, the researchers propose the utilization of a Support Vector Machine (SVM) model to develop an automated Twitter crawling system. The system aims to collect data related to weather in Indonesia by employing Twin, a Python-based Twitter scraping software. To overcome null geolocations, the study incorporates aliases created based on the common practice of Indonesian users mentioning the country's location in tweets. The results demonstrate that the SVM model, combined with automated smart crawling, achieves an 85% accuracy rate.

Using Recurrent Neural Network Structure and Multi-Head Attention with Convolution for Fraudulent Phone Text Recognition

Fraud cases have been a risk in society and people’s property security has been greatly threatened. In recent studies, many promising algorithms have been developed for social media offensive text recognition as well as sentiment analysis. These algorithms are also suitable for fraudulent phone text recognition. Compared to these tasks, the semantics of fraudulent words are more complex and more difficult to distinguish. Recurrent Neural Networks (RNN), the variants of RNN, Convolutional Neural Networks (CNN), and hybrid neural networks to extract text features are used by most text classification research. However, a single network or a simple network combination cannot obtain rich characteristic knowledge of fraudulent phone texts relatively. Therefore, a new model is proposed in this paper. In the fraudulent phone text, the knowledge that can be learned by the model includes the sequence structure of sentences, the correlation between words, the correlation of contextual semantics, the feature of keywords in sentences, etc. The new model combines a bidirectional Long-Short Term Memory Neural Network (BiLSTM) or a bidirectional Gate Recurrent United (BiGRU) and a Multi-Head attention mechanism module with convolution. A normalization layer is added after the output of the final hidden layer. BiLSTM or BiGRU is used to build the encoding and decoding layer. Multi-head attention mechanism module with convolution (MHAC) enhances the ability of the model to learn global interaction information and multi-granularity local interaction information in fraudulent sentences. A fraudulent phone text dataset is produced by us in this paper. The THUCNews data sets and fraudulent phone text data sets are used in experiments. Experiment results show that compared with the baseline model, the proposed model (LMHACL) has the best experiment results in terms of Accuracy, Precision, Recall, and F1 score on the two data sets. And the performance indexes on fraudulent phone text data sets are all above 0.94.

Поликодовые инструменты воздействия в антиковидной социальной рекламе (на примере рекламных кампаний в России и Турции)

In a comparative aspect, Russian and Turkish social advertising of the pandemic period is considered. Both similarities in the social communications of Russia and Turkey, and differences are noted: globalization has led to similarities in the topics of social advertising, tools to influence the audience, while the cultural code of countries, the population mentality have led to a number of communication differences, including in anti-COVID social advertising. The functional dynamics of social advertising in this period is noted: from educational to persuasive and inciting. Among the most common polycode tools of influence used in social advertising of coronavirus issues, the following are highlighted: visual images of typical characters, color, number, testemonium (celebrity participation), metaphorical modeling techniques, etc. Particular attention is paid to the frustration communication strategy, its tactics and techniques as one from the basic mechanisms for ensuring the effectiveness of social advertising texts. In addition, role model use of a responsible citizen who takes care of compliance with restrictions, self-isolation, is vaccinated, and does everything to stop the spread of the disease has become specific to social advertising of the coronavirus theme. The material for the study was the texts of Russian and Turkish social advertising dedicated to the problem of COVID-19 for 2020–2021.

Репрезентация концепта «Экология» в российской социальной рекламе

The author focuses on the content and functioning of the concept of “Ecology” in the texts of social advertising. The aim of the work was to identify and describe the content components of the concept “Ecology”. Modeling of the above-mentioned concept is carried out by analyzing its verbal and visual representations. The nuclear cognitive layer of the concept “Ecology” was described on the basis of lexicographic sources. The analysis of the texts of social advertising on environmental topics allowed to determine the corpus of linguistic means objectifying the concept of “Ecology”, as well as a set of artifacts visualizing its content. The expediency of using cognitive linguistics methods in the study of advertising discourse, in particular social advertising texts, is substantiated.

Realization of the educational potential of social advertising

The study of advertising discourse in modern Russian science is dedicated to a large number of works, but there are not enough specific studies of the social sector of advertising today. However, at the present time, due to dramatic changes in the political and sociocultural life of Russian society, this type of advertising is of particular importance. This paper is aimed at the issue of the specific status of social advertising texts within the framework of modern advertising discourse. An advertising announcement is seen as a polycode text intended for the public in general. The authors pay particular attention to the unity of form and content as a mechanism to influence the awareness and emotions of consumers of advertising. The material for analysis is the texts of street (urban) advertising. The functional-stylistic, cognitive, descriptive, semantic-grammatical, quantitative methods, as well as methods of discourse and comparative analysis are used. By analyzing a large number of texts, the high-impact potential of socially directed advertising texts is concluded. Identifying the semantic dominants of the texts of social advertising allows the authors to conclude about its disciplinary and teaching (educational) functions and consider these texts as one of the tools of human education. It is suggested that specially designed advertising texts can raise people in the spirit of traditional national values, to form the actual value meanings in the minds of those who perceive them. The paper gives examples of polycoded advertising texts functioning today in the living urban area.

Syrians in the Turkish curriculum, Social studies text book as a model: An analytical and descriptive study

يتناول البحث صورة السوريين وقضيتهم في المناهج الدراسية التركية في مراحل ما قبل التعليم الجامعي (الابتدائية والمتوسطة والثانوية). يحلل البحث نصوص الدروس المتعلقة بالقضية السورية والأنشطة اللاصفية المرتبطة بها في كتب الدراسات الاجتماعية التي احتضنت قضية السوريين في هذه المناهج. ويذهب البحث إلى أن صورة السوريين في الكتب الدراسية التركية محكومة بمنظورين أساسين، هما: المنظور الإنساني في المرحلتين الابتدائية والمتوسطة، والمنظور السياسي في المرحلة الثانوية. وهما منظوران يشكلان أُس السردية التربوية التركية تجاه القضية السورية، تبعًا لتطور العمر الزمني والعقلي لطلاب المدراس التركية السوريين والأتراك. كما يسعى البحث إلى الكشف عن الدور الذي تلعبه صورة اللاجئين السوريين وقضيتهم في كتب المناهج الدراسية التركية (مادة الدراسات الاجتماعية) من أثر في صناعة التكيف الاجتماعي بين الطلاب السوريين والأتراك.

TERM CONCEPTS FOR DISABILITY: SPECIFICS OF NOMINATION, FUNCTIONING AND TRANSLATION (BASED ON MATERIALS OF TURKISH)

Background. In linguistics only few works are dedicated to the study of the vocabulary to denote people with disabilities in the Turkish language (Y. Şişman, M. Öztürk, Z. Baykan, A. Demir, A. Efe), just as there are few specialized works in this filed in Ukrainian linguistics, who describe in their studies the problem of terminological irregularity and the lack of terms approved at the state level to denote disability. The relevance of this study is due to the need to popularize the principles of barrier-free society and inclusiveness, the large request for the translation of texts of rehabilitation and treatment, as well as the revitalization of relations between Ukraine and Turkey in these spheres. Methods. During the course of the study over two hundred term concepts used to denote disability and rehabilitation terms functioning from the end of the 19th to the beginning of the 21th century were analyzed with the complex methodology including methods of cognitive linguistics and sociolinguistic approach, the method of contextual analysis and the method of dictionary definitions analysis. Results. The terminology on disabilities in modern Turkish has disorganization that can be explained by such factors as: simultaneous usage of Turkish and foreign lexemes (Arabic Persian, English, French, Latin), euphemization of terms, orientation to international standards and agreements and, as a result, use of English lexemes etc. The vocabulary of international agreements and national legislation was found to differ in some cases. Quick formation of negative connotation is the main influencing factor on the terminology formation process and results in creation of a new replacing term without negative meaning. Conclusions. Summarizing the main difficult issues in translation we suggest to use the complex of methods and approaches, translation tactics and strategies to help for choosing an equivalent according to the type of discourse, such as using WHO classification for translation of medical documentation, taking into account the requirements of the legislation in force and amendments to it for official documents, being careful using periphrastic explanations, making the person as the main concept but not their characteristic. Adaptation for correctness is essential when translating social texts, advertising, fiction, excessive euphemization of concepts should be avoided when working with any type of text and terms for disability.

Editors’ Introduction

Editors’ Introduction

<em>DI BAWAH LANGIT TAK BERBINTANG</em> KARYA UTUY TATANG SONTANI: TINJAUAN SASTRA PERJALANAN CARL THOMPSON

Di Bawah Langit Tak Berbintang (DBLTB) by Utuy Tatang Sontani is a travel literature because it narrates travel, fulfills the formal-aesthetic characteristics of travel literature, and reconstructs travel experiences in a novelistic way. This study explains aspects of travel literature and the author's ideology with Thompson's theory of travel literature. The first problem data are verbal units in DBLTB which tell about self-other, movement, room, meeting, agenda, and writing, which are collected using the note-taking technique. Data ideology is narratives from social, cultural, and ideological texts, which are collected by literature study. The data are analyzed by content analysis and Laclau and Mouffe’s discourse analysis. This study shows that Utuy involved himself as I, a traveler in Indonesia and China. The journey makes him arrives at spaces, such as Bandung, Jakarta, Peking, Canton, Cengkareng, sanatoriums, and Cing Tao, and brings him meets with others, both people, places, and activities. In its journey, the dominant world is described subjectively, which then shows the author's agenda, namely and defends his ideology, namely individualism.

Akademik Türkçe Eğitimi Alan Uluslararası Öğrencilerin Yazılı Anlatımlarında Kullandıkları Terimler Üzerine Bir İnceleme

One of the primary goals of individuals who learn a language as a foreign language is to learn the most frequently used words in that language. In line with this goal, it is very important that the words with the highest frequency of use are included in the education and training process and that the course materials to be used are created according to this purpose. For this reason, it is important to examine the terms frequently used by learners of Turkish as a foreign language. The aim of this study is to determine the terms used in the written expressions of international students who learn Turkish as a foreign language and receive academic Turkish education. For this purpose, the survey model, one of the quantitative research designs, was used in the study. The sample of the study was formed by identifying 125 foreign students attending the academic Turkish course at Sakarya University TÖMER by criterion sampling method. Semi-structured interview forms created by the researchers were used as data collection tools. The data were analyzed using descriptive (quantitative) statistics. As a result of the study, it was observed that the most vocabulary items and terms in students' written expressions were found in social subject area texts. A total of 34 different terms were found to be used in common in all social, science and health subject areas.

Cyberbullying Body-Shaming Levels in Adolescence

Social media is a medium that teenagers very often use. Interaction media that users can use to easily interact, share, and social network without limits. The development of this social media can cause many impacts. This media will also have a harmful impact if used excessively. These problems arise in individuals who use the internet excessively, such as playing online games outside the limits of teaching to cause behavioral changes such as rudeness and aggression. Besides that, problems in the cyber world are commonly called cyberbullying. In addition, social media users easily express and publish their emotions and thoughts, including negative thoughts and emotions for others. The impact of this is the occurrence of bullying on social media. Cyberbullying, or cyber bullying, is a negotiation act that occurs and uses cyber media. Bullying often occurs through insults, threats, and humiliation on social media and text messages. The form of insult in cyberbullying is by bullying someone's physical appearance or better known as body shaming. Body shaming is a form of verbal emotional violence often not realized by the perpetrator because it is generally considered normal. Someone doing body shaming varies, from lighting the atmosphere, having fun, and inviting laughter to have reasons meant to insult

Reconsidering North Korean defectors: Social and semantic network analyses of YouTube videos on North Korean defectors

AbstractThis study investigates the North Korean defector phenomenon by approaching YouTube as an internet forum for public discourse, using the novel analytic approaches of social network analysis, text mining and semantic analysis. The research produced three main findings. First, individual YouTube content creators are most influential in the video networks pertaining to the subject of North Korean defectors. Second, on YouTube space, the image of North Korea tends to be negative because of the prevalence of defectors' testimony of their life experiences. Finally, such negative narratives of North Korea on YouTube might have a negative influence by blocking the reunification of Korea. In conclusion, this study suggests the South Korean government and other relevant global actors should conduct thorough and continuous examinations of North Korean defectors' perceptions of South Koreans and vice versa. This study calls for the international community to take further action to formulate proper policy instruments.

Using Social Media Data to Monitor Natural Disaster: A Multi Dimension Convolutional Neural Network Approach with Word Embedding

Social media has a significant role in natural disaster management, namely as an early warning and monitoring when natural disasters occur. Artificial intelligence can maximize the use of natural disaster social media messages for natural disaster management. The artificial intelligence system will classify social media message texts into three categories: eyewitness, non-eyewitness and don't-know. Messages with the eyewitness category are essential because they can provide the time and location of natural disasters. A common problem in text classification research is that feature extraction techniques ignore word meanings, omit word order information and produce high-dimensional data. In this study, a feature extraction technique can maintain word order information and meaning by using three-word embedding techniques, namely word2vec, fastText, and Glove. The result is data with 1D, 2D, and 3D dimensions. This study also proposes a data formation technique with new features by combining data from all word embedding techniques. The classification model is made using three Convolutional Neural Network (CNN) techniques, namely 1D CNN, 2D CNN and 3D CNN. The best accuracy results in this study were in the case of earthquakes 78.33%, forest fires 81.97%, and floods 78.33%. The calculation of the average accuracy shows that the 2D and 3D v1 data formation techniques work better than other techniques. Other results show that the proposed technique produces better average accuracy.

Ilf’s «Zapisnye Knizhki» [Sketch Books] of 1930s as the proof of social realistic discourse formation

The article theme is topical for the reason that Ilya Ilf in Zapisnye knizhki criticizes the socialist realism the art that propagandized and did not pay attention to the artistic expression quality and originality. In recent decades we can witness return of social realistic writing in the works of such authors as A. Ivanov, Z. Prilepin, K. Silvanova and E. Malisova. It appears that in the course of studying the classic Stalinist social realism and critical reflecting it is possible to understand certain patterns of the modern literature process. The research objective was to study Ilf's critique peculiarities and its objects. The article basic research methods comprise semiotic and intertextual analyses. The article beginning considers the context of Ilf's writing in 1930-s years. The stories by Ilf and Petrov, E. Zozulja and Barricady [Barricades] novel by P. Pavlenko were considered as the empiric material. As a result of the research, two thematic dominants of the writing were distinguished: 1) critical judgment of I. Ilfs literature colleagues who started working in social realistic manner in 1930-s years; 2) ironic attacks at the forming social realistic canon. Both of the writing thematic domains are polar opposite to Ilf and Petrov's artistic expression within the specified period. The coauthors created several social realistic texts, and some parts of Odnoetazhnaya America [One-storied America] are semantically compliant with the key Soviet ideology intentions. Thus, it is possible and necessary to distinguish between Ilfs independent creative working and the coauthors late works, where E. Petrov was an evident leader.