Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Faculty Publications Conference Paper Faculty Publications- Conference Papers Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Sharanya, R.; Singh, Shivangi; Jose, Deepa V Title A name given to the resource Emotion Trajectory Analysis and Model Comparison for Hate Speech and Radicalization Detection in Code-Mixed Platforms Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2025 Source A related resource from which the described resource is derived 2025 17th IEEE International Conference on Computational Intelligence and Communication Networks, CICN 2025;pp.1378-1383 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/CICN67655.2025.11368245" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/CICN67655.2025.11368245</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105034677241?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105034677241?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Sharanya R., Deemed to Be University, Dept. of Computer Science Christ, Bangalore, India; Singh S., Deemed to Be University, Dept. of Computer Science Christ, Bangalore, India; Jose D.V., Deemed to Be University, Dept. of Computer Science Christ, Bangalore, India Description An account of the resource The growing presence of multilingual and codemixed content on social media creates major challenges for automated emotion recognition and mental health support. In this work, we introduce an emotion-aware computational framework that processes code-mixed Indian language comments and predicts user emotions with high accuracy, followed by context-aware support suggestions. Our dataset comes from the AI4Bharat IndicNLP corpus [14] and the Dravidian-CodeMix sentiment dataset [15], featuring a variety of multilingual user comments. To maintain linguistic consistency, we translate the raw texts into English using Google Translator and then preprocess them through normalization, tokenization, and stopword removal. We use three advanced transformer-based models, DistilBERT (six emotions), DistilRoBERTa (seven emotions), and RoBERTa GoEmotions (27+ emotions), to categorize the emotions in the comments. We compare predictions across the models and select the most reliable label for each text, which is further verified through manual checks with human annotators. This process results in a curated dataset labeled with emotions and enriched with model provenance. With this dataset, we train a Logistic Regression classifier using TF-IDF features to create an efficient, explainable prediction pipeline. The system classifies emotions and provides tailored suggestions based on emotional states, improving user support in online interactions. Experimental results show the robustness of the pipeline and its ability to adapt to various code-mixed inputs. This study offers an integrated dataset-model-suggestion framework that advances emotion recognition in multilingual contexts and supports the creation of practical emotion-aware digital systems. 2025 IEEE. Subject The topic of the resource Code-Mixed Social Media; Computational Social Science; Early Detection; Emotion Dynamics; Hate Speech Detection; Natural Language Processing (NLP); Radicalization; Temporal Emotion Trajectories Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Relation A related resource ISBN: 979-833158733-8; Language A language of the resource English Type The nature or genre of the resource Conference paper Rights Information about rights held in and over the resource Restricted Access; Hardcopy may be available in the library Format The file format, physical medium, or dimensions of the resource online