Emotional Tonality Research Articles

Optimized Queuing Modeling in Multimodal Sentiment Analysis: An Examination and Application

This paper introduces an innovative queuing model tailored for multimodal sentiment analysis, designed to swiftly generate a preliminary score by prioritizing influential factors from the most valuable modalities. In a bid to yield reliable results in a compressed timeframe, this model meticulously processes data from the modality possessing the paramount effect factor, concurrently trimming down processing time by omitting data from lesser impactful modalities. This discerning approach allows for a dynamic adjustment of the weights assigned to various modalities based on their respective impact variables, culminating in precise and credible sentiment analysis outcomes. In an era where expediency and accuracy are at a premium, the proposed model stands out by ensuring that the sentiment analysis is not just rapid, but also robust and reliable, reflecting the true emotional tonality with a high degree of reliability. The model’s adaptability to fluctuating modalities, ensures its utility across diverse platforms and applications, making it a valuable tool for contemporary sentiment analysis tasks. Amidst a digital landscape that continually evolves, this queuing model for sentiment analysis exemplifies a significant leap forward, proffering enhanced efficiency, accuracy, and reliability in sentiment analysis endeavors.

ALGORITHM FOR DETECTION OF ABUSIVE CONTENT IN AUDIO CONTENT FOR IMPLEMENTATION IN OBJECT-ORIENTED INFORMATION SYSTEM

The paper proposes the basic principles of developing an object-oriented information system for detecting abusive content in Ukrainian-language audio content based on a new algorithm that uses statistical and neural network approaches to detect abusive content. Detecting offensive content in text and audio content is an urgent task, as it helps to create a safe and healthy environment for communication, especially in online platforms. Offensive content can harm the people who hear or read it and violate their rights. It can also have a negative impact on society, contributing to the spread of hatred and violence. To detect abusive speech in audio content, the proposed approach uses two key components: the use of dictionary methods and the analysis of the emotional tonality of utterances. A set of reviews was used as a dataset to determine the abusive component of the content, which was expanded by the authors by adding words of abuse. An object-oriented information system architecture written in the Python programming language in the PyCharm programming environment is proposed. The information system consists of a software module for training recurrent neural network models and further saving trained instances, and a software module for detecting abusive content in Ukrainian-language audio content using trained RNN models. Since the recurrent neural network is trained on a short text data set, the system is less efficient at identifying texts that have a larger number of words. In the example of the proposed approach, the accuracy of detecting offensive content is more than 90%. This means that the algorithm works correctly in the absence of offending highlights in the test data set. The results of the analysis of the effectiveness of the proposed approach show that in the vast majority of cases the conclusions regarding the acceptability of audio content based on the level of abuse are correct.

The impact of news about COVID-19 on the dynamics of the Russian stock market

Subject. The article addresses the Russian stock market during the COVID-19 pandemic. Objectives. The study aims at empirical substantiation of the influence of tonality of news about COVID-19 published in official sources and social networks, on the Russian stock market. Methods. We employ a set of methods and procedures to assess the sentiment of downloaded news texts and tweets and to model the dynamics of general and sectoral stock indices (bag-of-words method, Markov-switching GARCH models, evaluation of text tonality using EcSentiThemeLex dictionary). Results. The paper reveals the influence of the tone of coverage of events related to COVID-19 pandemic in news sources and social networks on changes in stock prices of Russian companies. We substantiated the existence of industry specifics in terms of the degree of influence of the tone of news and tweets on stock price dynamics. The findings can be used by investors and issuers to model and predict changes in securities prices, and complement the theory, by underpinning the significance of the tonality of messages in the news and social networks for the dynamics of the Russian stock market. Conclusions. Changes in the emotional tonality of news and social media posts about COVID-19 impacted the stock market of the Russian Federation. The models enabled to prove that in a volatile economy, not only the information published about the coronavirus is significant for the stock market, but also the dynamics of the number of cases.

К. Коровин –эмигрант: родной край в воспоминаниях художника

Konstantin Korovin is a famous Russian artist, one of the first Russian impressionists, as well as a theater decorator. The artist was highly sensitive to the beauties of the nature of his native land, and his oeuvre consists mostly of landscapes. In 1922, being at his senior age, Korovinwas forced to move to one of the centers of Russian emigration –Paris. Life away from his motherland becomes one of the reasons for the painter’s artistic crisis. It was during these difficult years that Korovin began to engage in literary work. Korovin writes memoirs, significant part of which is memories of the abandoned but much beloved motherland.The article provides a comparative study of pictorial and verbal figurativeness in Korovin’s works. The cycle On the Huntincludes a short story Frost, where the landscape plays a key role in the plot. Ananalysis of the poetics of figurativeness in this story reveals the features of pictorial impressionism in the verbal images. The article analyzes the techniques that the memoirist employs to create the image of his motherland. The key words-leitmotifs, color palette, lighting effects, and other means of creating a lyrical landscape are also analyzed. There are found to be some parallels between Korovin’s literary descriptions of landscapes and his landscape paintings of winter forest. The paper draws a conclusion about the similarity of impressionistic techniques in paintings and the story by Korovin; the features specific to literary (verbal) fig-urativeness are noted, for example, folklore traditions and allusions to Russian poetic classics, the change in the narrator’s points of view, changes in emotional tonality, which forms the basis of the lyrical plot in the story Frost.The methodological framework of the study is based on comparative-typologicaland system-semantic principles of analysis, with elements of genre and style analysis.

Функции на емотивния код в две книги на кръга „Мисъл“ – „Сън за щастие“ и „Идилии“

The article discusses some theoretical aspects of emotive meaning in the process of interpretation of the literary text. Emotive analysis is part of the basic structural analysis of the work and aims at functionally assisting, directing and clarifying its additional nuances and meanings. Finding the key to emotive codes and their dynamic interaction with other literary codes in the discussed work is a pre-requisite for the completion of the in-depth analysis of the text. The members of the „Misal” circle were particularly attentive to the ways in which emotion played an important role in the accomplishment of literary works. The study explores how the emotional tonality and the emotive code of „soft melancholy” play a key role in two works by the circle members – Dream of Happiness by Pencho Slaveykov and Idyllic Romances by Petko Todorov. The emotive code offers a new perspective of interpretation, exposing the inner tension within the form/content dichotomy of the text, in effect decoding its psychological meaning.

The Real-World Experiences of Persons With Multiple Sclerosis During the First COVID-19 Lockdown: Application of Natural Language Processing.

The increasing availability of "real-world" data in the form of written text holds promise for deepening our understanding of societal and health-related challenges. Textual data constitute a rich source of information, allowing the capture of lived experiences through a broad range of different sources of information (eg, content and emotional tone). Interviews are the "gold standard" for gaining qualitative insights into individual experiences and perspectives. However, conducting interviews on a large scale is not always feasible, and standardized quantitative assessment suitable for large-scale application may miss important information. Surveys that include open-text assessments can combine the advantages of both methods and are well suited for the application of natural language processing (NLP) methods. While innovations in NLP have made large-scale text analysis more accessible, the analysis of real-world textual data is still complex and requires several consecutive steps. We developed and subsequently examined the utility and scientific value of an NLP pipeline for extracting real-world experiences from textual data to provide guidance for applied researchers. We applied the NLP pipeline to large-scale textual data collected by the Swiss Multiple Sclerosis (MS) registry. Such textual data constitute an ideal use case for the study of real-world text data. Specifically, we examined 639 text reports on the experienced impact of the first COVID-19 lockdown from the perspectives of persons with MS. The pipeline has been implemented in Python and complemented by analyses of the "Linguistic Inquiry and Word Count" software. It consists of the following 5 interconnected analysis steps: (1) text preprocessing; (2) sentiment analysis; (3) descriptive text analysis; (4) unsupervised learning-topic modeling; and (5) results interpretation and validation. A topic modeling analysis identified the following 4 distinct groups based on the topics participants were mainly concerned with: "contacts/communication;" "social environment;" "work;" and "errands/daily routines." Notably, the sentiment analysis revealed that the "contacts/communication" group was characterized by a pronounced negative emotional tone underlying the text reports. This observed heterogeneity in emotional tonality underlying the reported experiences of the first COVID-19-related lockdown is likely to reflect differences in emotional burden, individual circumstances, and ways of coping with the pandemic, which is in line with previous research on this matter. This study illustrates the timely and efficient applicability of an NLP pipeline and thereby serves as a precedent for applied researchers. Our study thereby contributes to both the dissemination of NLP techniques in applied health sciences and the identification of previously unknown experiences and burdens of persons with MS during the pandemic, which may be relevant for future treatment.

Precarity as a mode of being-in-the-world in Michel Houellebecq’s Possibilité d’une Île

ABSTRACT Michel Houellebecq’s Anéantir has received mixed reviews. Houellebecq’s focus on loving intimacy and care for the elderly within the nuclear family allegedly showcases his transformation from an embittered critic of the capitalist status quo to an apolitical novelist interested in the private sphere. I argue that this criticism overlooks Houellebecq’s concerns about old age and love in his earlier novels and how they relate to his social critique. Particularly Houellebecq’s La Possibilité d’une île presents a critique of lonely precarity as the dominant mode of being-in-the-world today. Though critics of post-Fordism have already described post-Fordist forms of life as opportunistic, fearful, and cynical, Houellebecq adds that this uncertain marketized lifestyle also leads to bitterness that increases with old age. By confronting Houellebecq’s phenomenology of contemporary life to Heidegger’s analysis of Dasein, I argue that, whereas Heidegger highlights the role of anxiety and death in fostering a sense of meaning to human existence, Houellebecq rather argues that such an authentic confrontation with death has become impossible in contemporary culture and that love is instead the emotional tonality most responsive to the cultivation of a meaningful good life.

The peculiarities of using emoji pictograms in online communities with different frequency of use of obscene lexicon

The subject of this research is the use of pictograms for expressing emotions and feelings in network communication. The object is the comments in several communities in the popular among youth social network VKontakte. The goal of this article lies in the comparison of preferred emoji used by the users to express their emotions and feelings, who are part of the communities with different frequency of use of obscene lexicon. The hypothesis is advanced that the groups with different frequency of use of obscene lexicon differ in their emotional tonality and the emoji pictograms used for expressing emotions and feelings. The research is based on the method of survey in form of the questionnaire about the peculiarities of Internet preferences and most attractive communities in social network for the respondents; as well as the method of content analysis. The questionnaire survey involved 854 persons; the data on the frequency of use of emoji was collected on the example of 14 communities in VKontakte social network. It is determined that in communities with lesser use of obscene lexicon, the rating of emoji denoting positive (hedonic and affinity) emotions is higher. In communities with more obscene lexicon, the users equally use pictograms that express negative and positive emotion; most frequent negative emotions such denote anger and frustration, or melancholy, sadness. The acquired results can be applied in development of the methods for monitoring the moods of the users of network communication.

Іманентні складові жанру горор в українській літературі

The genesis and genre system of Ukrainian horror literature have been analyzed in the present article. Studying the origins of the horror genre in literature, one can find the combination of mysticism, a specific emotional tonality (mysteriousness, fear of the unknown) and mythological images, which acquire new features in the course of literary development. The dynamics of changes in the genre system of horror literature has been examined; the typological development of Ukrainian horror has been analyzed; the transformations of the established artistic matrix of horror literature and the mechanisms of preservation of genre memory have been traced. It has been proved that the presence of common genetic and typological genre features in different national literatures can be explained by the process of migration of plots, motifs and their variants. The genesis of the horror genre in the genre group of horror literature has been briefly presented; an attempt was made to systematize genre-forming elements. The peculiarity of horror as an artistic phenomenon that evolves from a stylistic technique to a genre has been demonstrated. The nature of the complex polysemantic construct of the horror genre has been revealed. The set of analyses such as descriptive, typological, hermeneutic, cultural-historical, mythopoetic, psychoanalytical, bibliographical, comparative, philological, structuralist, and intertextual has been used for the interpretation of the horror genre. The process of the creation of the latter is described as a gradual crystallisation of a relatively stable artistic structure, which evolves throughout the interplay of stable (a particular kind of chronotype, stable functions of characters) and dynamic elements.

Introduction: The politics of negative affects in post-Reform China

If there is such a thing as a dominant public sphere in post-reform China, its emotional tonality has often been described as overwhelmingly positive, as evidenced by the recent focus on “happiness” campaigns or state-promoted “positive energy.” This special section takes the prevalence of positivity as an invitation to investigate its opposites: what, in an authoritarian context, is the political work of negative affects such as bitterness, fear, shame, indifference, deflation, or trouble? Locating the articles within a broader literature on affect and emotion in anthropology and beyond, this introduction provides an overall framing for the collection. Based on the articles, it depicts the potential of negativity as both disruptive and generative, as affects work through their evaluative and propositional force which induces transformation while often evading repression.

Современное искусство Новосибирска в 2009–2019 годах

The work examines the contemporary art scene of Novosibirsk from 2009–2019. In the first part of the article we carry out a sociological analysis of the artistic life of the city and highlight such features as: the prevalence of self-organized forms of art presentation over institutional forms, non-publicity and “diffusivity” of a significant part of art practices. We also analyse the influence of these factors on the perception of art and discuss what kinds of methodological challenges they provoke. Further we give a brief overview of some significant exhibitions of the past decade (such as “Siberian Underground. 20 Years Later”, “Repetition of the Untrodden” etc.), examine artistic circles of the city and their transformation from 1990 to our time, discuss principles of their formation and the nature of interactions among them. We also propose a schematic representation of the artistic circles under consideration, their interactions and attractions from a historical point of view. The second part of the article examines the aesthetic features of contemporary art in Novosibirsk from 2009-2019. The transition from the art of the 00s and early 10s to the art of younger generations of the late 10s is characterized by a change in the emotional tonality: from vitality and expressivity to fragile and melancholic sensitivity, from political irony and grotesque to ethical complexity and vulnerability. When considering art of individual artists of the specified period we outline two possible ways of their analysis based on the allocation of a common motive: neo-expressionist and post-conceptual. The first of these is united by the motive of “toys” as a way of working with corporeality and doubleness (for example, in the works of Konstantin Skotnikov, the Cosmonauts art group, Denis Efremov, Alexei Grishchenko, Mayana Nasybullova, etc.). The post-conceptual line is presented through the works of such artists as: Alexander Limarev, Mikhail Karlov, the BERTOLLO art group, Irca Solza. Here we propose a unifying motive of “a game” as a dichotomy of rule systems and their failure that is viewed as an opportunity to conceive another world. In the conclusion of the article, we suggest that such an integrated approach to the analysis of regional art of the last decade is promising.

The Impact of Disclosure Sentiment on the Share Prices of Russian Companies

Information about companies published in a news feed is invariably tinted by emotional tonality. As such, resultingperceptions may influence the opinion of market players, and consequently affect the dynamics of a company’s shareprice. This study aims to evaluate various hypotheses about the impact of the tone of news items regarding dividends,capital expenditures, and development on the stock prices of Russian companies. Information disclosure is extensivelystudied, and there have been limited studies on the effect of disclosures on Russian companies. However, until now, therehave been no research studies which verify hypotheses on the influence of news sentiment on corporate share prices inthe Russian market.
 This analysis was conducted using data from 49 Russian public companies included in the Moscow exchange indexover the period from the end of 2017 to the beginning of 2019. To account for the proximate impact of news items onconsequential market phenomena, an event study methodology was applied in order to estimate and construct themodels of dependency of cumulative abnormal return (CAR) on news tone level, and control for financial and nonfinancialfactors.
 Our results provide evidence for the positive impact of the tone of news texts on the share prices of Russian companies.The increase in news tone by one standard deviation leads to a cumulative abnormal stock return increase of 0.26percentage points. This result is consistent with previous research conducted on data from developed stock markets.Moreover, the relationship between the tone or sentiment level of a news item and the stock price reaction is linear,without the diminishing marginal effect.
 Our conclusions should prompt companies to invest effort in delivering information in a tonally positive way,highlighting the most positive news. Investors, in turn, should rationally approach the interpretation of publishedinformation.

Using the Lenses of Emotion and Support to Understand Unemployment Discourse on Reddit

Unemployed individuals experience emotional upheaval and financial constraints, and they struggle to share their challenges and obtain support from their family members and social circles. While prior work has shown that social media platforms enable their users to safely share their turmoil, hardships, and emotional upheavals and seek support, little is known about how the unemployed use such platforms. Based on a mixed-methods analysis of data retrieved from unemployment communities on Reddit, our study reveals that redditors in these communities engage in exchanges that range from queries seeking information about job searching to discussions about sensitive topics such as the health and social implications of unemployment. Also, while redditors use mostly negative emotional tonality in their texts when initiating a new post, the comments in response provide considerable social support in the form of esteem, emotional, informational, network, and instrumental support. Based on these findings, we share the theoretical implications of our work and offer design

Influence of News Tonality on Credit Market during Sanctions Period

Russian economy was influenced by western sanctions in many spheres. Russian credit market was significantly impacted as well. The presented work suggests that except for the strict influence in form of financial restrictions and assets freezing, sanctions also had indirect impact. Emotional presentation of Russian sanctions in abroad media can be claimed as one of the indirect factors, which form banking management expectations of economic situation and influences people to have loans and place money into deposits. The aim of research is to estimate the influence of news about Russian sanctions tonality in foreign media on the level of credit and deposit interest rates in Russian commercial banks. To achieve this goal, the following hypotheses were claimed: there is a connection between the way in which sanctions against Russia are presented in foreign media and the level of interest rates; there is a difference in the impact of positive and negative news texts on the expectations, determining changes in interest rates. «Bag of words» technique and a special dictionary, which helps to identify the emotional tonality of the text, were used to achieve the declared aim. Advanced modeling of interest rates was carried out using the vector autoregression (VAR) model, supplemented by the construction of the impulse response function and the calculation of the rate dispersion decomposition. As a result, a hypothesis about the influence of news tonality on commercial bank interest rates’ was approved.

Невербальные маркеры эмоций для сентимент-анализа русскоязычных интернет-текстов

This article describes the initial stages of the project aiming to design a classifier of Internet texts in Russian by emotional tonality. To create a sentiment analysis algorithm that attributes texts to one of the 8 basic emotions according to Lovheim’s cube model, it is necessary to do the following: carefully select the language material for the training sample; label its tonality with the assistance of an independent expert; carry out an expert linguistic analysis of the data in order to determine the emotion markers; validate the markers using corpus analysis tools; and, subject to their quantitative significance in the emotion corpora, validate them in the work of the prototype classifier. The author examined the possibility of using non-verbal emotion markers as classification parameters. The linguistic analysis revealed two potential parameters: lexemes written in capital letters and numbers written in figures. Double validation of the markers identified allows us to determine which of them improves the accuracy of classification. The marker of writing numbers in figures leads to a 2 % increase in the overall accuracy of the sentiment analysis algorithm, as well as to a 7 % increase in the classification accuracy for the basic emotion of interest/excitement, and a 3 % increase for the basic emotions of surprise/startle and enjoyment/joy. It is noted that non-verbal markers are slightly less effective for the sentiment analysis of texts than lexical, semantic or punctuation markers, but are as much effective as syntactic markers. The results indicate the need to consider this type of markers along with verbal markers of emotions and explore in more detail concrete non-verbal markers as potential classifier parameters.

Conceptualization of time in internet-texts of different emotional tonality

The research is made in the frame of methodology of emotional text analysis – the computer technology allowing to classify texts according to the criterion of the emotion expressed in them. The paper focuses on specificity of verbal means used in texts of eight emotional classes to deal with the category of time. The data we used consist in 3900 Internet-texts from social network VKontakte assessed by 2000 informants on a crowdsource platform. We processed the raw data using the elements of mathematical modelling, and, a set of tools offered by Sketch Engine corpus manager platform. The hypothesis is that while experiencing an emotion, an individual feels the time differently and, consequently, speaks about it not in the same way. We paid a particular attention to the weight of the lexemes those semantics is connected with the idea of time in different emotional text classes.

Musical Code of Samuel Beckett’s Novel “Murphy”

The paper explores the ways in which music manifests itself on lexical-semantic, structural and rhythmic-syntactic levels of the novel “Murphy” (1938) by Samuel Beckett, whose Anglo- and Francophone writing is an attempt to synthesize prose and music. Beckett’s aesthetic ideas, his understanding of the expressivity of word and music were considerably influenced by Wittgenstein’s philosophy of linguistic skepticism and Schopenhauer’s vision of music as the only way of expressing the essence of the world.
 In his work, not only does Beckett combine the two forms of art through allusions and references, phonetic sound imitation or modeling of particular musical forms, but also makes an attempt to use the imagery of music and its ability to directly express feelings and thoughts, focusing on ‘semantic possibilities’ of music as a metaphor. Being sensitive to the sounding qualities of phrases in his works, Beckett perceived any sounds, even human ones, as music. He saturates the novel “Murphy” with auditory memories, rising and falling sounds, rhythms, melodies and musical categories, which enhance its musical effect. The diversity of musicality in Beckettian text is also manifested in the rhythmic organization, the presence of leitmotifs, and extensive use of verbal and structural repetitions.
 Therefore, Beckett’s method in “Murphy” involves using devices of musical expressiveness, as well as transforming the musical categories into metaphors of different experiences. Simultaneously, the rhythm of repetitions makes the emotional tonality of the work more distinct and creates the effect of intense movement of the consciousness.

A Research Article Assessing Social Media Activity Between 2016 and 2018 Relating to the Impact of Metastases in Prostate Cancer on Patients and Caregivers

About 15% of all cancer diagnoses in western Europe are for prostate cancer, and many cancer patients, caregivers, and healthcare professionals communicate over social media to discuss disease, treatments, side effects, concerns, and support. Social media listening can help identify unmet needs and fill gaps in patient treatment pathways. The authors wanted to understand the topics discussed, emotional tonality and sentiment of conversations, and specific behaviours exhibited. For this study, relevant mentions of prostate cancer were harvested using approved search syntax with social media listening technology. A representative sample across market datasets was used to uncover in-depth insights regarding emotions, key topics, perception, and behaviours, followed by an analysis of the qualitative aspects of the conversation to highlight emotions and behaviours related to the authors’ research objectives. About a quarter of the conversations were related to metastatic cancer, and non-metastatic cancer. Peaks coincided with social movements, such as ‘Movember’ and World Cancer Day. Most conversations about prostate cancer, whether metastatic or not, were driven by anxiety, fear, and worry. Throughout the patient journey, there was an underlying dread of disease progression, with peaks and troughs in emotion coinciding with diagnosis, metastases, treatment, and treatment failure. Patients often felt that they were left by their physicians to make their own decisions regarding treatment and used social media to communicate with their peers and caregivers to gain information. Via social media, patients shared information about disease status, treatment options, side effects, and quality of life, while offering each other emotional support.

Semiotics of threats: Discourse on the vulnerability of the Estonian identity card

This article analyses various e-threats that were expressed in media texts that focused on e-threat discourses concerning the Estonian identity card’s security risk in 2017. The discourse of cyberthreats contains strong and controversial meanings because the peculiarities of cyberspace remain intangible for average readers who do not possess expert knowledge regarding ICT. The wider aim of the paper is to suggest how the topic of e-threats could be given public coverage without fuelling irrational anxiety and unwarranted threat scenarios. Our theoretical basis combines the frameworks of the Copenhagen School of security studies and ideas of cultural semiotics. We explain the semiotic logic of phobophobia (i.e. the abstract concern with the devastating impacts of the collective feeling of fear) and the discourse of fear that is characterized by a significant reliance on analogies, drawing vague demarcation line between reference objects and the dominance of negative emotional tonality. Our study demonstrates that the main actors of threat and the consequences of the identity card’s security problems were associated with unknown hackers and the damaging of the reputation of Estonia as an e-state.

Использование текстов жанра «интернет-откровение» в контексте решения задач сентимент-анализа

The article aims to analyze the validity of Internet confession texts used as a source of training data set for designing computer classifier of Internet texts in Russian according to their emotional tonality. Thus, the classifier, backed by Lövheim’s emotional cube model, is expected to detect eight classes of emotions represented in the text or to assign the text to the emotionally neutral class. The first and one of the most important stages of the classifier creation is the training data set selection. The training data set in Machine Learning is the actual dataset used to train the model for performing various actions. The internet text genres that are traditionally used in sentiment analysis to train two or three tonalities classifiers are twits, films and market reviews, blogs and financial reports. The novelty of our project consists in designing multiclass classifier that requires a new non-trivial training data. As such, we have chosen the texts from public group Overheard in Russian social network VKontakte. As all texts show similarities, we united them under the genre name “Internet confession”. To feature the genre, we applied the method of narrative semiotics describing six positions forming the deep narrative structure of “Internet confession”: Addresser – a person aware of her/his separateness from the society; Addressee – society / public opinion; Subject – a narrator describing his / her emotional state; Object – the person’s self-image; Helper – the person’s frankness; Adversary – the person’s shame. The above mentioned genre features determine its primary advantage – a qualitative one – to be especially focused on the emotionality while more traditional sources of textual data are based on such categories as expressivity (twits) or axiological estimations (all sorts of reviews). The structural analysis of texts under discussion has also demonstrated several advantages due to the technological basis of the Overheard project: the text hashtagging prevents the researcher from submitting the whole collection to the crowdsourcing assessment; its size is optimal for assessment by experts; despite their hyperbolized emotionality, the texts of Internet confession genre share the stylistic features typical of different types of personal internet discourse. However, the narrative character of all Internet confession texts implies some restrictions in their use within sentiment analysis project.