--- title: "Social Psychology — papers" description: "Social Psychology: 129 papers of the Elamur Research library · page 1 of 3 · 1–25, the most cited first — our summary of each, its ideas, references and…" canonical: "https://research.elamur.ai/free/en/shelves/psychology/social-psychology/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/shelves/psychology/social-psychology/) [home](https://md.research.elamur.ai/free/en/) / [shelves](https://md.research.elamur.ai/free/en/shelves/) / [Psychology](https://md.research.elamur.ai/free/en/shelves/psychology/) / Social Psychology # 💭 Social Psychology 129 papers · page 1 of 3 · 1–25 · the most cited first · [all shelves](https://md.research.elamur.ai/free/en/shelves/) Social Psychology is a subfield of Psychology in the OpenAlex classification of science. The topics most of its papers here are on: «Mental Health via Writing», «Humor Studies and Applications», «Social Robot Interaction and HRI». ## Papers **1** [2](https://md.research.elamur.ai/free/en/shelves/psychology/social-psychology/page/2/) [3](https://md.research.elamur.ai/free/en/shelves/psychology/social-psychology/page/3/) [next →](https://md.research.elamur.ai/free/en/shelves/psychology/social-psychology/page/2/) 1. [**An Argument for Basic Emotions**Paul Ekman*1992 · 9,903 citations*](https://md.research.elamur.ai/free/en/papers/ekman-1992-argument-basic-emotions/) 2. [**Predicting the Type and Target of Offensive Posts in Social Media**Marcos Zampieri, Shervin Malmasi, Preslav Nakov, et al.*2019 · 1,118 citations*](https://md.research.elamur.ai/free/en/papers/zampieri-2019-predicting-type-target-offensive-posts/) 3. [**SemEval-2018 Task 1: Affect in Tweets**Saif Mohammad, Felipe Bravo-Marquez, Mohammad Salameh, et al.*2018 · 1,094 citations*](https://md.research.elamur.ai/free/en/papers/mohammad-2018-semeval-2018-task-1-affect/) 4. [**TweetEval: Unified Benchmark and Comparative Evaluation for Tweet Classification**Francesco Barbieri, Jose Camacho-Collados, Leonardo Neves, et al.*2020 · 952 citations*](https://md.research.elamur.ai/free/en/papers/barbieri-2020-tweeteval-unified-benchmark-comparative-evaluation/) 5. [**Quantifying Mental Health Signals in Twitter**Glen Coppersmith, Mark Dredze, Craig Harman*2014 · 823 citations*](https://md.research.elamur.ai/free/en/papers/coppersmith-2014-quantifying-mental-health-signals-twitter/) 6. [**ClinicalBERT: Modeling Clinical Notes and Predicting Hospital Readmission**Kexin Huang, Jaan Altosaar, Rajesh Ranganath*2019 · 798 citations*](https://md.research.elamur.ai/free/en/papers/huang-2019-clinicalbert-modeling-clinical-notes-predicting/) 7. [**Discriminating Gender on Twitter**John D. Burger, John Henderson, George Kim, et al.*2011 · 632 citations*](https://md.research.elamur.ai/free/en/papers/burger-2011-discriminating-gender-twitter/) 8. [**Role-Play with Large Language Models**Murray Shanahan, Kyle McDonell, Laria Reynolds*2023 · 606 citations*](https://md.research.elamur.ai/free/en/papers/shanahan-2023-role-play-large-language-models/) 9. [**Benchmarking Aggression Identification in Social Media**Ritesh Kumar, Atul Kr. Ojha, Shervin Malmasi, et al.*2018 · 510 citations*](https://md.research.elamur.ai/free/en/papers/kumar-2018-benchmarking-aggression-identification-social-media/) 10. [**EmoNet: Fine-Grained Emotion Detection with Gated Recurrent Neural Networks**Muhammad Abdul-Mageed, Lyle Ungar*2017 · 487 citations*](https://md.research.elamur.ai/free/en/papers/mageed-2017-emonet-fine-grained-emotion-detection/) 11. [**Inference-Time Intervention: Eliciting Truthful Answers from a Language Model**Kenneth Li, Oam Patel, Fernanda Viegas, et al.*2023 · 473 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-inference-time-intervention-eliciting-truthful/) 12. [**Evaluating Large Language Models in Theory of Mind Tasks**Michal Kosinski*2023 · 467 citations*](https://md.research.elamur.ai/free/en/papers/kosinski-2023-evaluating-large-language-models-theory/) 13. [**CARER: Contextualized Affect Representations for Emotion Recognition**Elvis Saravia, Hsien-Chi Toby Liu, Yen-Hao Huang, et al.*2018 · 448 citations*](https://md.research.elamur.ai/free/en/papers/saravia-2018-carer-contextualized-affect-representations-emotion/) 14. [**CLPsych 2015 Shared Task: Depression and PTSD on Twitter**Glen Coppersmith, Mark Dredze, Craig Harman, et al.*2015 · 415 citations*](https://md.research.elamur.ai/free/en/papers/coppersmith-2015-clpsych-2015-shared-task-depression/) 15. [**SemEval-2019 Task 3: EmoContext Contextual Emotion Detection in Text**Ankush Chatterjee, Kedhar Nath Narahari, Meghana Joshi, et al.*2019 · 411 citations*](https://md.research.elamur.ai/free/en/papers/chatterjee-2019-semeval-2019-task-3-emocontext/) 16. [**A Computational Approach to Understanding Empathy Expressed in Text-Based Mental Health Support**Ashish Sharma, Adam Miner, David Atkins, et al.*2020 · 408 citations*](https://md.research.elamur.ai/free/en/papers/sharma-2020-computational-approach-understanding-empathy-expressed/) 17. [**Depression and Self-Harm Risk Assessment in Online Forums**Andrew Yates, Arman Cohan, Nazli Goharian*2017 · 402 citations*](https://md.research.elamur.ai/free/en/papers/yates-2017-depression-self-harm-risk-assessment/) 18. [**That's So Annoying!!!: A Lexical and Frame-Semantic Embedding Based Data Augmentation Approach to Automatic Categorization of Annoying Behaviors using #petpeeve Tweets**William Yang Wang, Diyi Yang*2015 · 395 citations*](https://md.research.elamur.ai/free/en/papers/wang-2015-that-s-so-annoying-lexical/) 19. [**Large-scale Analysis of Counseling Conversations: An Application of Natural Language Processing to Mental Health**Tim Althoff, Kevin Clark, Jure Leskovec*2016 · 390 citations*](https://md.research.elamur.ai/free/en/papers/althoff-2016-large-scale-analysis-counseling-conversations/) 20. [**Learning from Bullying Traces in Social Media**Jun-Ming Xu, Kwang-Sung Jun, Xiaojin Zhu, et al.*2012 · 382 citations*](https://md.research.elamur.ai/free/en/papers/xu-2012-learning-bullying-traces-social-media/) 21. [**Knowledge-Enriched Transformer for Emotion Detection in Textual Conversations**Peixiang Zhong, Di Wang, Chunyan Miao*2019 · 372 citations*](https://md.research.elamur.ai/free/en/papers/zhong-2019-knowledge-enriched-transformer-emotion-detection/) 22. [**WASSA-2017 Shared Task on Emotion Intensity**Saif Mohammad, Felipe Bravo-Marquez*2017 · 369 citations*](https://md.research.elamur.ai/free/en/papers/mohammad-2017-wassa-2017-shared-task-emotion/) 23. [**Directed Acyclic Graph Network for Conversational Emotion Recognition**Weizhou Shen, Siyue Wu, Yunyi Yang, et al.*2021 · 345 citations*](https://md.research.elamur.ai/free/en/papers/shen-2021-directed-acyclic-graph-network-conversational/) 24. [**Developing Age and Gender Predictive Lexica over Social Media**Maarten Sap, Gregory Park, Johannes Eichstaedt, et al.*2014 · 296 citations*](https://md.research.elamur.ai/free/en/papers/sap-2014-developing-age-gender-predictive-lexica/) 25. [**Expert, Crowdsourced, and Machine Assessment of Suicide Risk via Online Postings**Han-Chin Shing, Suraj Nair, Ayah Zirikly, et al.*2018 · 290 citations*](https://md.research.elamur.ai/free/en/papers/shing-2018-expert-crowdsourced-machine-assessment-suicide/) **1** [2](https://md.research.elamur.ai/free/en/shelves/psychology/social-psychology/page/2/) [3](https://md.research.elamur.ai/free/en/shelves/psychology/social-psychology/page/3/) [next →](https://md.research.elamur.ai/free/en/shelves/psychology/social-psychology/page/2/) Updated 24 October 2026 - [← previous subfield Experimental and Cognitive Psychology](https://md.research.elamur.ai/free/en/shelves/psychology/experimental-and-cognitive-psychology/) - [↑ back to Psychology](https://md.research.elamur.ai/free/en/shelves/psychology/)