Profiling a set of personality traits of text author: what our words reveal about us

Authorship profiling, i.e. revealing information about an unknown author by analyzing their text, is a task of growing importance. One of the most urgent problems of authorship profiling (AP) is selecting text parameters which may correlate to an author’s personality. Most researchers’ selection of these is not underpinned by any theory. This article proposes an approach to AP which applies neuroscience data. The aim of the study is to assess the probability of self-destructive behaviour of an individual via formal parameters of their texts. Here we have used the “Personality Corpus”, which consists of Russian-language texts. A set of correlations between scores on the Freiburg Personality Inventory scales that are known to be indicative of self-destructive behaviour (“Spontaneous Aggressiveness”, “Depressiveness”, “Emotional Lability”, and “Composedness”) and text variables (average sentence length, lexical diversity etc.) has been calculated. Further, a mathematical model which predicts the probability of self-destructive behaviour has been obtained

Character analysis of oral activity: contact profiling

The article presents the results of our observations on syntactic, semantic and plot peculiarities of oral language activity, we find it justified to consider the above mentioned parameters as identification criteria for discovering characterological differences of Ukrainian-speaking and Russian-speaking objects of contact profiling. It describes the connection between mechanisms of psychological defenses as the character structural components, and agentive and non-agentive speech constructions, internal and external predicates. Localized and described plots of oral narratives inherent to representatives of different character types

A Methodological Approach to Understanding Emotional States Using Textual Data

In the age of digital communication, an abundance of textual data is generated daily through various channels, such as social media, emails, and chat applications. This wealth of textual information has opened up new avenues for understanding and evaluating the emotional states of individuals. Text analysis, a powerful tool in natural language processing (NLP), has emerged as a valuable method for gaining insights into the emotions, sentiments, and psychological well-being of people. This article explores the method of text analysis and its application in evaluating the emotional state of individuals through textual data

Drawing Elena Ferrante's Profile. Workshop Proceedings, Padova, 7 September 2017

Elena Ferrante is an internationally acclaimed Italian novelist whose real identity has been kept secret by E/O publishing house for more than 25 years. Owing to her popularity, major Italian and foreign newspapers have long tried to discover her real identity. However, only a few attempts have been made to foster a scientific debate on her work. In 2016, Arjuna Tuzzi and Michele Cortelazzo led an Italian research team that conducted a preliminary study and collected a well-founded, large corpus of Italian novels comprising 150 works published in the last 30 years by 40 different authors. Moreover, they shared their data with a select group of international experts on authorship attribution, profiling, and analysis of textual data: Maciej Eder and Jan Rybicki (Poland), Patrick Juola (United States), Vittorio Loreto and his research team, Margherita Lalli and Francesca Tria (Italy), George Mikros (Greece), Pierre Ratinaud (France), and Jacques Savoy (Switzerland). The chapters of this volume report the results of this endeavour that were first presented during the international workshop Drawing Elena Ferrante's Profile in Padua on 7 September 2017 as part of the 3rd IQLA-GIAT Summer School in Quantitative Analysis of Textual Data. The fascinating research findings suggest that Elena Ferrante\u2019s work definitely deserves \u201cmany hands\u201d as well as an extensive effort to understand her distinct writing style and the reasons for her worldwide success

Temporal word embeddings for dynamic user profiling in Twitter

The research described in this paper focused on exploring the domain of user profiling, a nascent and contentious technology which has been steadily attracting increased interest from the research community as its potential for providing personalised digital services is realised. An extensive review of related literature revealed that limited research has been conducted into how temporal aspects of users can be captured using user profiling techniques. This, coupled with the notable lack of research into the use of word embedding techniques to capture temporal variances in language, revealed an opportunity to extend the Random Indexing word embedding technique such that the interests of users could be modelled based on their use of language. To achieve this, this work concerned itself with extending an existing implementation of Temporal Random Indexing to model Twitter users across multiple granularities of time based on their use of language. The product of this is a novel technique for temporal user profiling, where a set of vectors is used to describe the evolution of a Twitter user’s interests over time through their use of language. The vectors produced were evaluated against a temporal implementation of another state-of-the-art word embedding technique, the Word2Vec Dynamic Independent Skip-gram model, where it was found that Temporal Random Indexing outperformed Word2Vec in the generation of temporal user profiles

Profiling commenters on mental health-related online forums : a methodological example focusing on eating disorder-related commenters

Background Understanding the characteristics of commenters on mental health-related online forums is vital for the development of effective psychological interventions in these communities. The way in which commenters interact can enhance our understanding of their characteristics. Objective Using eating disorder-related (EDR) forums as an example, this study details a methodology that aimed to determine subtypes of mental health-related forums, and profile their commenters based on the other forums to which they contributed. Methods The researchers identified all public EDR-forums (with ≥500 contributing commenters between March 2017 and February 2018) on a large online discussion platform (Reddit). A mixed-methods approach comprising network analysis with community-detection, text-mining and manual review identified subtypes of EDR-forums. For each subtype, another network analysis with community-detection was conducted using the EDR-forum commenter-overlap between 50 forums on which the commenters also commented. The topics of forums in each detected community were then manually reviewed to identify the shared interests of each subtype of EDR-forum commenters. Results Six subtypes of EDR-forums were identified, to which 14024 commenters had contributed. The results focus on two subtypes – pro-eating disorder, and thinspiration – and communities of commenters within both subtypes. Within the pro-eating disorder subtype, three communities of commenters were detected that related to the body and eating, mental health, and women, appearance and mixed topics. Regarding the thinspiration group, 78% of commenters had also commented on pornographic forums, and 17% had contributed to pro-eating disorder forums. Conclusions The article exemplifies a methodology that provides insight into subtypes of mental health-related forums, and the characteristics of their commenters. The findings have implications for future research, and online psychological interventions. With the publicly available data and code provided, researchers can easily reproduce the analyses, or utilise the methodology to investigate other mental health-related forums

On the distinction between metonymy and vertical polysemy in encyclopaedic semantics

In cognitive linguistics, metonymy is seen as a fundamental cognitive process where one conceptual entity affords access to another closely associated one. Cases of vertical polysemy have also often been treated as instances of metonymy (see e.g. Radden and Kövecses, 1999). In vertical polysemy a lexical form designates two or more senses that are in a relationship of categorial inclusion – e.g. dog ‘canine’, ‘male canine’. In this paper I present an account of cases of vertical polysemy from the point of view of domain-based encyclopaedic semantics as described in Langacker (1987). I claim that the domain configurations which underlie the broader and narrower meanings of vertical polysemes are very different from those involved in cases of metonymy. Croft (1993) argues that from a Langackerian viewpoint, metonymy involves a shift in the salience of two domains that form parts of a domain matrix against which a given concept is profiled. In cases of vertical polysemy, on the other hand, the relationship between the broader and narrower meanings may be effected in a number of different ways, none of which involve the kind of domain configurations found in metonymy. For example, the narrower ‘male canine’ sense of dog makes reference to an additional domain of SEX, a domain which is not an essential part of the domain structure of the broader ‘canine’ meaning