Search Results for author:
Found 15 papers, 3 papers with code
Users Hate Blondes: Detecting Sexism in User Comments on Online Romanian News
Romania ranks almost last in Europe when it comes to gender equality in political representation, with about 10${%$ fewer women in politics than the E. U.
Capturing Changes in Mood Over Time in Longitudinal Data Using Ensemble Methodologies
This paper presents the system description of team BLUE for Task A of the CLPsych 2022 Shared Task on identifying changes in mood and behaviour in longitudinal textual data.
EXPRES Corpus for A Field-specific Automated Exploratory Study of L2 English Expert Scientific Writing
After applying lexical sophistication, lexical variation and syntactic complexity formulae, significant differences between disciplines were identified, mainly that research articles from Lv journals have higher lexical complexity, but lower syntactic complexity than articles from Hv journals; while academic vocabulary proved to have discipline specific variation.
Reading Between the Frames: Multi-Modal Depression Detection in Videos from Non-Verbal Cues
Depression, a prominent contributor to global disability, affects a substantial portion of the population.
Automatic Extraction of the Romanian Academic Word List: Data and Methods
This paper presents the methodology and data used for the automatic extraction of the Romanian Academic Word List (Ro-AWL).
Utilizing ChatGPT Generated Data to Retrieve Depression Symptoms from Social Media
The task consists of retrieving and ranking Reddit social media sentences that convey symptoms of depression from the BDI-II questionnaire.
It's Just a Matter of Time: Detecting Depression with Time-Enriched Multimodal Transformers
In this work, we propose a flexible time-enriched multimodal transformer architecture for detecting depression from social media posts, using pretrained models for extracting image and text embeddings.
An End-to-End Set Transformer for User-Level Classification of Depression and Gambling Disorder
This work proposes a transformer architecture for user-level classification of gambling addiction and depression that is trainable end-to-end.
Life is not Always Depressing: Exploring the Happy Moments of People Diagnosed with Depression
In this work, we explore the relationship between depression and manifestations of happiness in social media.
BLUE at Memotion 2.0 2022: You have my Image, my Text and my Transformer
Memes are prevalent on the internet and continue to grow and evolve alongside our culture.
Cultural Vocal Bursts Intensity Prediction
Meme Classification
+1
Sequence-to-Sequence Lexical Normalization with Multilingual Transformers
Our results show that while word-level, intrinsic, performance evaluation is behind other methods, our model improves performance on extrinsic, downstream tasks through normalization compared to models operating on raw, unprocessed, social media text.
A Psychologically Informed Part-of-Speech Analysis of Depression in Social Media
In this work, we provide an extensive part-of-speech analysis of the discourse of social media users with depression.
Early Risk Detection of Pathological Gambling, Self-Harm and Depression Using BERT
Early risk detection of mental illnesses has a massive positive impact upon the well-being of people.
An Exploratory Analysis of the Relation Between Offensive Language and Mental Health
In this paper, we analyze the interplay between the use of offensive language and mental health.
Detecting Early Onset of Depression from Social Media Text using Learned Confidence Scores
Computational research on mental health disorders from written texts covers an interdisciplinary area between natural language processing and psychology.
