Corpus Of Interactions Research Articles

Large Language Models and Genomics for Summarizing the Role of microRNA in Regulating mRNA Expression.

microRNA (miRNA)-messenger RNA (mRNA or gene) interactions are pivotal in various biological processes, including the regulation of gene expression, cellular differentiation, proliferation, apoptosis, and development, as well as the maintenance of cellular homeostasis and pathogenesis of numerous diseases, such as cancer, cardiovascular diseases, neurological disorders, and metabolic conditions. Understanding the mechanisms of miRNA-mRNA interactions can provide insights into disease mechanisms and potential therapeutic targets. However, extracting these interactions efficiently from a huge collection of published articles in PubMed is challenging. In the current study, we annotated a miRNA-mRNA Interaction Corpus (MMIC) and used it for evaluating the performance of a variety of machine learning (ML) models, deep learning-based transformer (DLT) models, and large language models (LLMs) in extracting the miRNA-mRNA interactions mentioned in PubMed. We used the genomics approaches for validating the extracted miRNA-mRNA interactions. Among the ML, DLT, and LLM models, PubMedBERT showed the highest precision, recall, and F-score, with all equal to 0.783. Among the LLM models, the performance of Llama-2 is better when compared to others. Llama 2 achieved 0.56 precision, 0.86 recall, and 0.68 F-score in a zero-shot experiment and 0.56 precision, 0.87 recall, and 0.68 F-score in a three-shot experiment. Our study shows that Llama 2 achieves better recall than ML and DLT models and leaves space for further improvement in terms of precision and F-score.

Communicative efficiency in multimodal language directed at children and adults.

The ecology of human communication is face to face. In these contexts, speakers dynamically modify their communication across vocal (e.g., speaking rate) and gestural (e.g., cospeech gestures related in meaning to the content of speech) channels while speaking. What is the function of these adjustments? Here we ask whether speakers dynamically make these adjustments to increase communicative success, and decrease cognitive effort while speaking. We assess whether speakers modulate word durations and produce iconic (i.e., imagistically evoking properties of referents) gestures depending on the predictability of each word they utter. Predictability is operationalized as surprisal and computed from computational language models trained on corpora of child-directed, or adult-directed language. Using data from a novel corpus (Ecological Language Corpus) of naturalistic interactions between adult-child (aged 3-4), and adult-adult, we show that surprisal predicts speakers' multimodal adjustments and that some of these effects are modulated by whether the comprehender is a child or an adult. Thus, communicative efficiency applies generally across vocal and gestural communicative channels not being limited to structural properties of language or vocal modality. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Word frequency and cognitive effort in turns-at-talk: turn structure affects processing load in natural conversation.

Frequency distributions are known to widely affect psycholinguistic processes. The effects of word frequency in turns-at-talk, the nucleus of social action in conversation, have, by contrast, been largely neglected. This study probes into this gap by applying corpus-linguistic methods on the conversational component of the British National Corpus (BNC) and the Freiburg Multimodal Interaction Corpus (FreMIC). The latter includes continuous pupil size measures of participants of the recorded conversations, allowing for a systematic investigation of patterns in the contained speech and language on the one hand and their relation to concurrent processing costs they may incur in speakers and recipients on the other hand. We test a first hypothesis in this vein, analyzing whether word frequency distributions within turns-at-talk are correlated with interlocutors' processing effort during the production and reception of these turns. Turns are found to generally show a regular distribution pattern of word frequency, with highly frequent words in turn-initial positions, mid-range frequency words in turn-medial positions, and low-frequency words in turn-final positions. Speakers' pupil size is found to tend to increase during the course of a turn at talk, reaching a climax toward the turn end. Notably, the observed decrease in word frequency within turns is inversely correlated with the observed increase in pupil size in speakers, but not in recipients, with steeper decreases in word frequency going along with steeper increases in pupil size in speakers. We discuss the implications of these findings for theories of speech processing, turn structure, and information packaging. Crucially, we propose that the intensification of processing effort in speakers during a turn at talk is owed to an informational climax, which entails a progression from high-frequency, low-information words through intermediate levels to low-frequency, high-information words. At least in English conversation, interlocutors seem to make use of this pattern as one way to achieve efficiency in conversational interaction, creating a regularly recurring distribution of processing load across speaking turns, which aids smooth turn transitions, content prediction, and effective information transfer.

Nonverbal Communication in Classroom Interaction and Its Role in Italian Foreign Language Teaching and Learning

The purpose of this study is to present the state of the art of recent research on nonverbal communication in L2 classroom interaction, in particular on teachers’ and students’ gestures, and then focus on a case of gestures in an L2 Italian classroom. A corpus of video-recorded interactions (CLODIS) were analyzed to answer the following research question: How do L2 Italian native teachers behave when addressing international students? Are there differences with what has been observed in other foreign language (L2) teaching contexts? Both previous data-based research on multimodality in L2 classes and the analysis on CLODIS show that teachers select and coordinate multiple semiotic modes as interactional resources to complete various teaching tasks. Furthermore, Italian native teachers use not only the typical pedagogical gestures (both iconic and metaphorical), but also culturally specific emblems that may cause misunderstandings or inappropriate mirroring effects. For these reasons, it is important that L2 teachers develop a good multimodal awareness, especially if they teach their mother tongue to foreign students and if they belong to a “contact culture”, as is the case observed in L2 Italian classes.

Moving Towards (and Away From) Possible Discussions About Dying

The article examines a corpus of palliative care interactions recorded in a large UK hospice. It focuses on a collection of patient possible allusions to disease progression and end of life and examines their companions’ (i.e., accompanying family members and friends) subsequent actions. These actions implement various interactional projects that are coherent with the sequence of actions and broader activity underway. They share the outcome that they steer the interaction away from the possibility of immediately elaborating on the patient’s allusion, and of making matters related to disease progression or end of life explicit (despite these being relevant possibilities).

Emotion detection in educational dialogues by transfer learning

Emotion detection in educational dialogues, particularly within student-teacher interactions, has become a crucial research area for improving the learning experience. In this paper, we employ two models, one generic Bidirectional Encoder Representations from Transformers (BERT) and the Emotion detection model Robustly Optimized BERT Approach (EmoRoBERTa), to automatically classify emotions in a corpus of student-teacher chat interactions. Then subsequently, we validate these classifications using a scheme based on oracles, employing two generative large language models (ChatGPT and Bard). Experiments on emotion detection in dialogues between students and teachers revealed that EmoRoBERTa exhibited a reasonable level of agreement with the oracles, while ChatGPT demonstrated the highest consistency with EmoRoBERTa’s predictions. Furthermore, we identified the impact of specific words on emotion classification, offering insights into the decision-making process of these models. The results not only highlight the prominent presence of emotions like approval, gratitude, curiosity, disapproval, amusement, confusion, remorse, joy, and surprise but also provide substantial support for the utilization of the proposed emotion detection model to enhance the student learning environment. Exploring the emotional aspects of educational dialogues holds the potential to enhance instruction methods, provide timely assistance to students in need, and create an improved learning atmosphere.

Flexible gold standards for transcription factor regulatory interactions in Escherichia coli K-12: architecture of evidence types.

Post-genomic implementations have expanded the experimental strategies to identify elements involved in the regulation of transcription initiation. Here, we present for the first time a detailed analysis of the sources of knowledge supporting the collection of transcriptional regulatory interactions (RIs) of Escherichia coli K-12. An RI groups the transcription factor, its effect (positive or negative) and the regulated target, a promoter, a gene or transcription unit. We improved the evidence codes so that specific methods are incorporated and classified into independent groups. On this basis we updated the computation of confidence levels, weak, strong, or confirmed, for the collection of RIs. These updates enabled us to map the RI set to the current collection of HT TF-binding datasets from ChIP-seq, ChIP-exo, gSELEX and DAP-seq in RegulonDB, enriching in this way the evidence of close to one-quarter (1329) of RIs from the current total 5446 RIs. Based on the new computational capabilities of our improved annotation of evidence sources, we can now analyze the internal architecture of evidence, their categories (experimental, classical, HT, computational), and confidence levels. This is how we know that the joint contribution of HT and computational methods increase the overall fraction of reliable RIs (the sum of confirmed and strong evidence) from 49% to 71%. Thus, the current collection has 3912 reliable RIs, with 2718 or 70% of them with classical evidence which can be used to benchmark novel HT methods. Users can selectively exclude the method they want to benchmark, or keep for instance only the confirmed interactions. The recovery of regulatory sites in RegulonDB by the different HT methods ranges between 33% by ChIP-exo to 76% by ChIP-seq although as discussed, many potential confounding factors limit their interpretation. The collection of improvements reported here provides a solid foundation to incorporate new methods and data, and to further integrate the diverse sources of knowledge of the different components of the transcriptional regulatory network. There is no other genomic database that offers this comprehensive high-quality architecture of knowledge supporting a corpus of transcriptional regulatory interactions.

English Code-Mixings in WhatsApp interactions among Spanish adolescents and their orthographic competence

Aims: The widespread use of computer-mediated communication (CMC) among adolescents has favored the creation of a newly written code called digitalk. This new code includes, among other characteristics, the use of foreign words as textisms, mainly anglicisms. These textisms also serve as a mark of identity among young speakers. The aim of this paper is twofold: first, to describe which are the more frequent anglicisms used by Spanish adolescents in their CMC and the code-mixing pathways of inclusion; second, to examine the possible influence between the use of anglicisms in the CMC of Spanish adolescents and their orthographic competence. Method: Based on an exploratory methodology, a corpus of interactions through WhatsApp of a group of adolescents attending Compulsory Secondary Education in a region of southern Spain has been analyzed. Data analysis: Sketch Engine software was used for corpus analysis, presenting the normalized frequency (1/1,000) of textisms, misspellings, and multimodal elements. Finally, for the descriptive statistical analysis of the data and for the bivariate correlation analysis applying Pearson’s coefficient, IBM SPSS v.26 software was used. Findings: The results indicate that young people use English Code-Mixings (ECM) as discursive framers with an expressive aim and as a sign of belonging to a specific community of speakers. Moreover, no positive correlation is observed between the use of these ECMs and a lower orthographic competence. Implications: ECMs show an important pragmatic function in CMC among Spanish adolescents. Furthermore, they are one of the elements that have been incorporated into the digital norm of Spanish and can be used in Compulsory Education as a resource for the acquisition of communicative competence in adolescents along with other textisms. Originality: This is the first research that analyzes the frequency and function of anglicisms in Spanish CMC and their impact on the orthographic competence of Spanish adolescents.

Reaching beneath the tip of the iceberg: A guide to the Freiburg Multimodal Interaction Corpus

Abstract Most corpora tacitly subscribe to a speech-only view filtering out anything that is not a ‘word’ and transcribing the spoken language merely orthographically despite the fact that the “speech-only view on language is fundamentally incomplete” (Kok 2017, 2) due to the deep intertwining of the verbal, vocal, and kinesic modalities (Levinson and Holler 2014). This article introduces the Freiburg Multimodal Interaction Corpus (FreMIC), a multimodal and interactional corpus of unscripted conversation in English currently under construction. At the time of writing, FreMIC comprises (i) c. 29 h of video-recordings transcribed and annotated in detail and (ii) automatically (and manually) generated multimodal data. All conversations are transcribed in ELAN both orthographically and using Jeffersonian conventions to render verbal content and interactionally relevant details of sequencing (e.g. overlap, latching), temporal aspects (pauses, acceleration/deceleration), phonological aspects (e.g. intensity, pitch, stretching, truncation, voice quality), and laughter. Moreover, the orthographic transcriptions are exhaustively PoS-tagged using the CLAWS web tagger (Garside and Smith 1997). ELAN-based transcriptions also provide exhaustive annotations of re-enactments (also referred to as (free) direct speech, constructed dialogue, etc.) as well as silent gestures (meaningful gestures that occur without accompanying speech). The multimodal data are derived from psychophysiological measurements and eye tracking. The psychophysiological measurements include, inter alia, electrodermal activity or GSR, which is indicative of emotional arousal (e.g. Peräkylä et al. 2015). Eye tracking produces data of two kinds: gaze direction and pupil size. In FreMIC, gazes are automatically recorded using the area-of-interest technology. Gaze direction is interactionally key, for example, in turn-taking (e.g. Auer 2021) and re-enactments (e.g. Pfeiffer and Weiss 2022), while changes in pupil size provide a window onto cognitive intensity (e.g. Barthel and Sauppe 2019). To demonstrate what opportunities FreMIC’s (combination of) transcriptions, annotations, and multimodal data open up for research in Interactional (Corpus) Linguistics, this article reports on interim results derived from work-in-progress.

The Italian Epistemic Disclaimer Non so [I Don’t Know] in a Corpus of Gynaecological Interactions

Viewing conversations from an epistemic perspective involves analysing how participants navigate their knowledge, handle uncertainty, and address their lack of knowledge. This article focuses on the use of epistemic disclaimers, i.e., linguistic expressions that speakers employ to indicate uncertainty or lack of knowledge, in a collection of Italian gynaecological conversations throughout pregnancy. Specifically, the study examines the occurrences, features, and pragmatic functions of the epistemic disclaimers, with a specific focus on Non so, which is the Italian equivalent of “I don’t know” in English, the most extensively researched epistemic disclaimer. The study aims to (1) investigate the types and frequency of uncertain and unknowing epistemic disclaimers in the gynaecological corpus and (2) identify their characteristics and pragmatic functions. The primary findings indicate that epistemic disclaimers are primarily used to convey unknowledge rather than uncertainty. However, while patients use more epistemic disclaimers than doctors, they mainly use them to communicate unknowledge, whereas doctors mainly use them to express uncertainty. Regardless, their usage does not appear problematic in conversational terms since the topics for which they are used fall outside the domains of knowledge of each party.

Self-disclosures in online crisis counselling: levelling asymmetries while maintaining client-focus

ABSTRACT While self-disclosures are often cautioned against in social work practice, research on crisis helplines has shown that self-disclosures can be connected to positive outcomes. Based on conversation analysis of 38 online chats, drawn from a larger corpus of crisis helpline interactions, the current paper unpacks the details of how trained volunteer counsellors use self-disclosures to support work with clients. The findings demonstrate how vague and general self-disclosures maintain a focus on the client and offer clients opportunities rather than requirements to learn. In online talk about suicide, self-disclosures are beneficial because they provide a way to display investment and understanding, which may be more difficult without verbal resources. On the other hand, self-disclosures often require clients to wait for counsellors to type in a time-sensitive situation. Showing this, the study contributes knowledge on interactional resources in online communication, in particular the work whereby counsellors and clients manage asymmetries connected to who knows, who can share, and who decides about courses of actions.

Interactional features in second language classroom discourse: variations across novice and experienced language teachers

Abstract Classrooms provide a context in which teachers and learners co-construct meaning in light of their sociocultural understandings and profiles. However, to date, few studies have scrutinized the way such profiles contribute to teachers’ classroom discourse. Informed by the methodological framework of conversation analysis and drawing upon a corpus of 20-h naturally-occurring classroom interactions, the present study examined variations in novice and experienced teachers’ classroom discourse in providing opportunities for learner interlanguage development. The study relied on Walsh’s (2006. Investigating classroom discourse. Routledge) conceptualization of classroom context mode in the data collection and analysis stages. Quantitative and qualitative analyses of the data revealed that the experienced teachers’ discourse was marked by greater simultaneity and immediacy characteristics targeted at learner engagement in comparison to novice teachers. The study findings highlight variations between the two groups across a range of discursive constructions and provide implications for enhancing novice teachers’ classroom discourse.

Authentic questions as prompts for productive and constructive sequences: A pragmatic approach to classroom dialogue and argumentation

Goal. The problem of the authenticity of teacher questions has not received sufficient attention from educational researchers interested in the intersection between dialogue and argumentation. In this paper, we adopt a definition of authentic questions as dialogical units that prompt teacher-student interactions that are both productive (i.e., several students participating) and constructive (i.e., students produce arguments of high complexity). Our goal is to analyze whether and how specific types of dialogue prompts can encourage students’ engagement in more sophisticated argumentative interactions, as manifested through the construction of high-complexity arguments. Method. We describe the implementation of our analytical approach to a large corpus of classroom interactions from five European countries. The corpus was segmented into dialogical sequences, which were then coded according to the argumentation dialogue goal expressed in the sequence. We also coded students’ arguments according to Toulmin’s elements and distinguished between low- and high-complexity arguments from a structural point of view. Findings. Our findings show the predominance of the so-called Discovery questions as prompts that are both productive and constructive and Inquiry questions as prompts of argumentative constructive interactions. We discuss the importance of these findings for teacher professional development purposes.

Turn-taking in human face-to-face interaction is multimodal: gaze direction and manual gestures aid the coordination of turn transitions.

Human communicative interaction is characterized by rapid and precise turn-taking. This is achieved by an intricate system that has been elucidated in the field of conversation analysis, based largely on the study of the auditory signal. This model suggests that transitions occur at points of possible completion identified in terms of linguistic units. Despite this, considerable evidence exists that visible bodily actions including gaze and gestures also play a role. To reconcile disparate models and observations in the literature, we combine qualitative and quantitative methods to analyse turn-taking in a corpus of multimodal interaction using eye-trackers and multiple cameras. We show that transitions seem to be inhibited when a speaker averts their gaze at a point of possible turn completion, or when a speaker produces gestures which are beginning or unfinished at such points. We further show that while the direction of a speaker's gaze does not affect the speed of transitions, the production of manual gestures does: turns with gestures have faster transitions. Our findings suggest that the coordination of transitions involves not only linguistic resources but also visual gestural ones and that the transition-relevance places in turns are multimodal in nature. This article is part of a discussion meeting issue 'Face2face: advancing the science of social interaction'.

The expression of emotions in online medical consultations: a comprehensive Spanish-English analysis

Doctor-patient interpersonality strategies have evolved considerably in recent years, mainly due to the increase in telephone and online consultations generated by the Covid-19 pandemic. In this type of interaction, the control and expression of emotions have a crucial influence on the adequacy and effectiveness of communication. Remote interaction makes this affective exchange even more complex than in face-to-face consultations. The present study aims to configure a comprehensive model for analysing the affective domain in virtual medical consultations, useful for English and Spanish patients and learners. With this aim, the most recognised theories on professional interpersonality are reviewed and applied to a corpus of doctor-patient interactions in Peninsular Spanish and British English, extracted from representative forums on the Internet. The analysis highlights how specific stance and register variation mechanisms positively and negatively influence the emotional domain in these communicative exchanges. The proposed model allows significant contrastive findings on the occurrence and intensity of sentiment markers in both languages. The results illustrate how doctors in Spanish favour a more cautious, detached and predictable encounter, while doctors in English use a greater number and variety of attitudinal strategies to achieve engagement, empathy and emotional comfort.

Context-Dependent Learning of Linguistic Disjunction.

What are the constraints, cues, and mechanisms that help learners create successful word-meaning mappings? This study takes up linguistic disjunction and looks at cues and mechanisms that can help children learn the meaning of or. We first used a large corpus of parent-child interactions to collect statistics on or uses. Children started producing or between 18-30 months and by 42 months, their rate of production reached a plateau. Second, we annotated for the interpretation of disjunction in child-directed speech. Parents used or mostly as exclusive disjunction, typically accompanied by rise-fall intonation and logically inconsistent disjuncts. But when these two cues were absent, disjunction was generally not exclusive. Our computational modeling suggests that an ideal learner could successfully interpret an English disjunction (as exclusive or not) by mapping forms to meanings after partitioning the input according to the intonational and logical cues available in child-directed speech.

The CABB dataset: A multimodal corpus of communicative interactions for behavioural and neural analyses

We present a dataset of behavioural and fMRI observations acquired in the context of humans involved in multimodal referential communication. The dataset contains audio/video and motion-tracking recordings of face-to-face, task-based communicative interactions in Dutch, as well as behavioural and neural correlates of participants’ representations of dialogue referents. Seventy-one pairs of unacquainted participants performed two interleaved interactional tasks in which they described and located 16 novel geometrical objects (i.e., Fribbles) yielding spontaneous interactions of about one hour. We share high-quality video (from three cameras), audio (from head-mounted microphones), and motion-tracking (Kinect) data, as well as speech transcripts of the interactions. Before and after engaging in the face-to-face communicative interactions, participants’ individual representations of the 16 Fribbles were estimated. Behaviourally, participants provided a written description (one to three words) for each Fribble and positioned them along 29 independent conceptual dimensions (e.g., rounded, human, audible). Neurally, fMRI signal evoked by each Fribble was measured during a one-back working-memory task. To enable functional hyperalignment across participants, the dataset also includes fMRI measurements obtained during visual presentation of eight animated movies (35 min total). We present analyses for the various types of data demonstrating their quality and consistency with earlier research. Besides high-resolution multimodal interactional data, this dataset includes different correlates of communicative referents, obtained before and after face-to-face dialogue, allowing for novel investigations into the relation between communicative behaviours and the representational space shared by communicators. This unique combination of data can be used for research in neuroscience, psychology, linguistics, and beyond.

Adaptation and validation of two annotation scales for assessing social skills in a corpus of multimodal collaborative interactions.

Behavioral observation scales are important for understanding and assessing social skills. In the context of collaborative problem-solving (CPS) skills, considered essential in the 21st century, there are no validated scales in French that can be adapted to different CPS tasks. The aim of this study is to adapt and validate, by annotating a new video corpus of dyadic interactions that we have collected, two observational scales allowing us to qualitatively assess CPS skills: the Social Performance Rating Scale (SPRS) and the Social Skills of Collaboration Scale (SSC). The construct validity of these two scales was assessed by exploratory factor analysis and inter-item correlations. We also checked inter-judge agreement using inter-class correlation coefficients. Internal consistency was determined using Cronbach's alpha and convergent and divergent validity by assessing correlations between the two scales and measures of depression and alexithymia. Finally, the discriminative properties of the two scales were analyzed by comparing the scores obtained by a group of anxious individuals and a non-anxious control group. The results show that our two scales have excellent inter-item correlations. Internal consistency is excellent (alpha SPRS =0.90; SSC = 0.93). Inter-rater agreement ranged from moderate to high. Finally, convergent validity was significant with the alexithymia scale, as was divergent validity with the depression scale. Anxious individuals had lower scores on both scales than non-anxious individuals. Both scales show good psychometric properties for assessing social skills relevant to different collaborative tasks. They also identify individuals with difficulties in social interaction. Thus, they could allow monitoring the effectiveness of training social skills useful in CPS.

Coding relevance

Relevance is one of the crucial criteria for assessing the quality of argumentation in education. In argumentation and education, relevance has never been analyzed or coded. While several theories have included in their analysis some indicators of cohesion or clarity, this characteristic of dialogue and discourse has never been addressed as a distinct phenomenon. This paper builds on the existing studies in linguistic and philosophy to advance criteria for assessing relevance, which in turn can be used for developing a coding scheme for evaluating dialogue moves. Relevance is analyzed starting from the pragmatic principle that dialogue moves are instruments for pursuing a common dialogical goal. Starting from a classification of the possible types of dialogue moves, defined based on the possible dialogue that they propose or continue, five criteria of relevance are illustrated, capturing both pragmatic and topical coherence. Such criteria are shown to provide guidance for distinguishing not only relevant from irrelevant moves, but also the degrees of strength of relevance. The theoretical framework and the assessment criteria will be illustrated through a corpus of classroom interactions collected in Portuguese middle-grade schools.

’Doing Questioning’ in the Emergency Department (ED)

ABSTRACT Eliciting information from patients is fundamental to medical professionals’ capacity to deliver good healthcare outcomes in Emergency Departments (EDs). There are different kinds of utterances that “do questioning”, and health professionals can variously attend to the medical agenda and the interpersonal aspects of their interactions with those attending the ED in the way that they construct these utterances. We investigate a corpus of ED interactions to determine the prevalence and range of utterances produced by doctors and directed at patients that “do questioning.” We developed a questioning utterance typology, informed by previous research on the formulation of such utterances and extended according to observations of our data. We subsequently manually coded 4,355 questioning utterances and report the variety of forms that such utterances can take, considering how these are distributed across doctors at different levels of seniority. We found that doctors at different seniority levels favored similar questioning utterance types and the most frequently used appeared to restrict the contributions of patients. We conclude that our extended typology of questioning utterances has value for understanding the ways in which doctors may encourage patients to provide more extensive responses.