•BPD is associated with actively using a diverse range of words for negative emotion.•The association between BPD and negative emotion word use is insensitive to context.•These findings likely ...reflect extensive experience with negative emotion.•Extensive but inflexible attention to negative emotion may drive dysfunction in BPD.
Emotion dysregulation is a characteristic central to borderline personality disorder (BPD). Valuably, verbal behaviour can provide a unique perspective for studying emotion dysregulation in BPD, with recent research suggesting that the varieties of emotion words one actively uses (i.e., active emotion vocabularies EVs) reflect habitual experience and potential dysregulation therein. Accordingly, the present research examined associations between BPD and active EVs across two studies.
Study 1 (N = 530) comprised a large non-clinical sample recruited from online forums, whereby BPD traits were measured via self-report. Study 2 (N = 64 couples) consisted of mixed-gender romantic couples in which the woman had a BPD diagnosis, as well as a control group of couples. In both studies, participants’ verbal behaviours were analysed to calculate their active EVs.
Results from both studies revealed BPD to be associated with larger negative EV (i.e., using a broad variation of unique negative emotion words), which remained robust when controlling for general vocabulary size and negative affect word frequency in Study 2. The association between BPD and negative EV was insensitive to context.
Limitations of this research include: 1) the absence of a clinical control group; 2) typical constraints surrounding word-counting approaches; and 3) the cross-sectional design (causality cannot be inferred).
Our findings contribute to BPD theory as well as the broader language and emotion literature. Importantly, these findings provide new insight into how individuals manifesting BPD attend to and represent their emotional experiences, which could be used to inform clinical practice.
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•We assessed spontaneous discourse in Parkinson’s disease (PD) with automatized tools.•Compared to controls, patients used fewer action concepts and more subordinators.•Analysis of grammar choices ...allowed classifying patients and controls above chance.•The incidence of word repetitions predicted the patients’ level of motor impairment.•Naturalistic discourse features may index the integrity of specific neural networks.
To assess the impact of Parkinson’s disease (PD) on spontaneous discourse, we conducted computerized analyses of brief monologues produced by 51 patients and 50 controls. We explored differences in semantic fields (via latent semantic analysis), grammatical choices (using part-of-speech tagging), and word-level repetitions (with graph embedding tools). Although overall output was quantitatively similar between groups, patients relied less heavily on action-related concepts and used more subordinate structures. Also, a classification tool operating on grammatical patterns identified monologues as pertaining to patients or controls with 75% accuracy. Finally, while the incidence of dysfluent word repetitions was similar between groups, it allowed inferring the patients’ level of motor impairment with 77% accuracy. Our results highlight the relevance of studying naturalistic discourse features to tap the integrity of neural (and, particularly, motor) networks, beyond the possibilities of standard token-level instruments.
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43.
I Say, You Say, We Say Stewart, Angela E.B.; Vrzakova, Hana; Sun, Chen ...
Proceedings of the ACM on human-computer interaction,
11/2019, Volume:
3, Issue:
CSCW
Journal Article
Peer reviewed
Collaborative problem solving (CPS) is a crucial 21st century skill; however, current technologies fall short of effectively supporting CPS processes, especially for remote, computer-enabled ...interactions. In order to develop next-generation computer-supported collaborative systems that enhance CPS processes and outcomes by monitoring and responding to the unfolding collaboration, we investigate automated detection of three critical CPS process ? construction of shared knowledge, negotiation/coordination, and maintaining team function ? derived from a validated CPS framework. Our data consists of 32 triads who were tasked with collaboratively solving a challenging visual computer programming task for 20 minutes using commercial videoconferencing software. We used automatic speech recognition to generate transcripts of 11,163 utterances, which trained humans coded for evidence of the above three CPS processes using a set of behavioral indicators. We aimed to automate the trained human-raters' codes in a team-independent fashion (current study) in order to provide automatic real-time or offline feedback (future work). We used Random Forest classifiers trained on the words themselves (bag of n-grams) or with word categories (e.g., emotions, thinking styles, social constructs) from the Linguistic Inquiry Word Count (LIWC) tool. Despite imperfect automatic speech recognition, the n-gram models achieved AUROC (area under the receiver operating characteristic curve) scores of .85, .77, and .77 for construction of shared knowledge, negotiation/coordination, and maintaining team function, respectively; these reflect 70%, 54%, and 54% improvements over chance. The LIWC-category models achieved similar scores of .82, .74, and .73 (64%, 48%, and 46% improvement over chance). Further, the LIWC model-derived scores predicted CPS outcomes more similar to human codes, demonstrating predictive validity. We discuss embedding our models in collaborative interfaces for assessment and dynamic intervention aimed at improving CPS outcomes.
Automated writing evaluation (AWE) has been used increasingly to provide feedback on student writing. Previous research typically focused on its inter-rater reliability with human graders and ...validation frameworks. The limited body of research has only discussed students' attitudes or perceptions in general. A systematic investigation of the driving factors contributing to students' acceptance is still lacking. This study proposes an extended technology acceptance model (TAM) to identify the environmental, individual, educational, and systemic factors that influence college students' acceptance of AWE feedback and examine how they affect college students' usage intention. Structural equation modeling (SEM) was used to analyze the quantitative survey data from 448 Chinese college students who had used AWE feedback for at least one semester. Results revealed that students' behavioral intention to use AWE feedback was affected by the subjective norm, facilitating conditions, perceived trust, AWE self-efficacy, cognitive feedback, and system characteristics. Among them, subjective norm, perceived trust, and cognitive feedback positively influenced perceived usefulness; facilitating conditions, AWE self-efficacy, and system characteristics were significant determinants of perceived ease of use; anxiety played no role for experienced users. Implications from these findings to AWE developers and practitioners are further elaborated.
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Skipgram modelling is a technique for generating multi-word terms that preserves some of the sequentiality and flexibility of the language. However, in some cases the number of skipgrams generated ...may become excessive as the distance between words increases. Moreover, this distance is often not taken into account when evaluating the terms that are generated. In this paper we propose a technique for efficient skipgram generation and filtering, and a weighing scheme that takes into account the distance between terms, giving more importance to those closer. We will apply and evaluate these proposals in the task of sentiment analysis.
Hope speech detection in Spanish García-Baena, Daniel; García-Cumbreras, Miguel Ángel; Jiménez-Zafra, Salud María ...
Language resources and evaluation,
12/2023, Volume:
57, Issue:
4
Journal Article
Peer reviewed
Open access
In recent years, systems have been developed to monitor online content and remove abusive, offensive or hateful content. Comments in online social media have been analyzed to find and stop the spread ...of negativity using methods such as hate speech detection, identification of offensive language or detection of abusive language. We define hope speech as the type of speech that is able to relax a hostile environment and that helps, gives suggestions and inspires for good to a number of people when they are in times of illness, stress, loneliness or depression. Detecting it automatically, in order to give greater diffusion to positive comments, can have a very significant effect when it comes to fighting against sexual or racial discrimination or when we intend to foster less bellicose environments. In this article we perform a complete study on hope speech, analyzing existing solutions and available resources. In addition, we have generated a quality resource, SpanishHopeEDI, a new Spanish Twitter dataset on LGBT community, and we have conducted some experiments that can serve as a baseline for further research.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Corpus linguistics studies real-life language use on the basis of a text corpus, drawing on both quantitative and qualitative text analysis techniques. This article seeks to bridge the gap between ...the social sciences and linguistics by introducing the techniques of corpus linguistics to the field of computer-aided text analysis. The article first discusses the differences between corpus linguistics and computer-aided text analysis, which is divided into computer-aided content analysis and computer-aided interpretive textual analysis. It then outlines the techniques of corpus linguistics for exploring textual data. In an exemplary analysis of letters to shareholders, the article demonstrates how these techniques can be applied to compare letters to shareholders from two different years. The article concludes with a discussion of the strengths and limitations of corpus linguistics for management and organization studies.
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Recently, masked autoencoders have demonstrated their feasibility in extracting effective image and text features (e.g., BERT for natural language processing (NLP) and MAE in computer vision (CV)). ...This study investigates the potential of applying these techniques to vision-and-language representation learning in the medical domain. To this end, we introduce a self-supervised learning paradigm, multi-modal masked autoencoders (M
AE). It learns to map medical images and texts to a joint space by reconstructing pixels and tokens from randomly masked images and texts. Specifically, we design this approach from three aspects: First, taking into account the varying information densities of vision and language, we employ distinct masking ratios for input images and text, with a notably higher masking ratio for images; Second, we utilize visual and textual features from different layers for reconstruction to address varying levels of abstraction in vision and language; Third, we develop different designs for vision and language decoders. We establish a medical vision-and-language benchmark to conduct an extensive evaluation. Our experimental results exhibit the effectiveness of the proposed method, achieving state-of-the-art results on all downstream tasks. Further analyses validate the effectiveness of the various components and discuss the limitations of the proposed approach. The source code is available at https://github.com/zhjohnchan/M3AE.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
O objetivo deste trabalho é analisar e descrever como as relações de tempo se configuram na Língua Brasileira de Sinais (libras). O fenômeno se constitui pela relação entre dois Estados de Coisas ...(doravante EsCo), um temporal e outro principal. A investigação é realizada à luz de uma abordagem tipológico-funcional (CROFT, 2001; CRISTOFARO, 2003). Tomamos como base dados extraídos do Corpus de libras da UFSC, anotados por meio do software ELAN (EUDICO Linguistic Annotador). Nossa análise visa ilustrar as propriedades morfossintáticas das construções temporais, mostrando que (a.) a anteposição do EsCo temporal é a ordem não marcada; e outro, de ordem semântica; (b.) o EsCo temporal pode expressar os valores semânticos de: anterioridade, posterioridade e simultaneidade; e (c.) há dependência semântica entre os EsCo temporal e principal.Palavras-chave: Estado de Coisas; oração de tempo; Funcionalismo; tipologia linguística; Sintaxe; libras.
Facebook remains the most important platform where social media editors package and try to ‘sell’ media outlets’ online news articles to audiences. In one of the first studies of its kind, we assess ...how this practice was effectuated during the first year of the COVID-19 pandemic. We use computational analysis to determine the polarity, subjectivity and use of some linguistics features in the status messages of 140,359 Facebook posts of 17 mainstream and alternative news titles from Flanders (Belgium) between March 2020 and 2021. Among other things, we find that status messages score considerably higher than headlines in terms of polarity and subjectivity, and that they, along with the use of question and interrogation marks, peaked in the first months of the pandemic. We contextualise our findings within existing scholarship and wider trends in increasingly digitised and globalised media societies.
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