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An Optimized Hybrid Neural Network Model for Detecting Depression among Twitter Users

Also, a user-friendly GUI is presented to the user that loads the trained neural network in no time and can be used to analyze the users' state of depression.  ...  The aim of this research work is to provide an algorithm to evaluate users' sentiment on Twitter in a way better than all other existing techniques  ...  [16] is a popular lexicon-based algorithm for social media.  ... 
doi:10.35940/ijitee.j9590.0881019 fatcat:5o5j663pdfb2bhq7vsz3iced44

Affective Conditioning on Hierarchical Networks applied to Depression Detection from Transcribed Clinical Interviews [article]

D. Xezonaki, G. Paraskevopoulos, A. Potamianos, S. Narayanan
2020 arXiv   pre-print
In this work we propose a machine learning model for depression detection from transcribed clinical interviews.  ...  71.6 and 68.6 F1 scores respectively.  ...  Acknowledgements We would like to thank psychologists Evangelia Prassopoulou and Anastasios Panopoulos who gave us a thorough insight into Depressive disorder and their psychological approach on the treatment  ... 
arXiv:2006.08336v1 fatcat:sjdhxvuyzjg4tieqjgpxvucvfm

Affective Conditioning on Hierarchical Attention Networks Applied to Depression Detection from Transcribed Clinical Interviews

Danai Xezonaki, Georgios Paraskevopoulos, Alexandros Potamianos, Shrikanth Narayanan
2020 Interspeech 2020  
In this work we propose a machine learning model for depression detection from transcribed clinical interviews.  ...  Index Terms: depression detection, clinical interviews, recurrent neural networks, hierarchical attention networks, affective lexica 1  ...  Based on this observation, we employ external linguistic knowledge about the affective content of words. These features can be obtained by sources created by human experts.  ... 
doi:10.21437/interspeech.2020-2819 dblp:conf/interspeech/XezonakiPPN20 fatcat:z7znex4pyveexak4k6pavuykxi

EmoMix+: An Approach of Depression Detection Based on Emotion Lexicon for Mobile Application

Ran Li, Yuanfei Zhang, Lihua Yin, Zhe Sun, Zheng Lin, Peng Fu, Weiping Wang, Gang Shi, Ahmed A. Abd El-Latif
2022 Security and Communication Networks  
Emotional characteristics are an effective feature in detecting depression, but the traditional emotion lexicon has limitations in detecting depression and ignores many depression words.  ...  Therefore, we build an emotion lexicon for depression to further study the differences between healthy users and patients with depression.  ...  Acknowledgments is work was supported in part by the National Natural Science Foundation of China (no. 62002077) and the Guangdong Basic and Applied Basic Research Foundation (no. 2020A1515110385).  ... 
doi:10.1155/2022/1208846 fatcat:ojoc6tgz5bftxcp7tcm22te63m


2021 Zenodo  
Several researches focus on specific public sentiments for example Malays, English, Arabic, Chinese and Korean.  ...  The identification of mental health can be detected using several data domains such as: sensors, text, structured data, and multi-modal system use.  ...  depression Nafiz Al Asad et al, 2019 [57] Social media content and sentiment analysis on consumer security breaches Depression Detection Text English Analyze the level of depression based  ... 
doi:10.5281/zenodo.5392869 fatcat:226k3nzxcrf6rkzvkkw2fwobya

Suicidal Ideation and Mental Disorder Detection with Attentive Relation Networks [article]

Shaoxiong Ji, Xue Li, Zi Huang, Erik Cambria
2021 arXiv   pre-print
This paper enhances text representation with lexicon-based sentiment scores and latent topics and proposes using relation networks to detect suicidal ideation and mental disorders with related risk indicators  ...  Early detection of mental disorders and suicidal ideation from social content provides a potential way for effective social intervention.  ...  Acknowledgments The authors would like to thank Philip Resnik for providing the UMD Reddit Suicidality Dataset and Mark Dredze for providing the dataset in the CLPsych 2015 shared task.  ... 
arXiv:2004.07601v3 fatcat:amgogcdh75hshhg6klv25lqzdu

Predicting Mental Health Problems with Automatic Identification of Metaphors

Nan Shi, Dongyu Zhang, Lulu Li, Shengjun Xu
2021 Journal of Healthcare Engineering  
In this paper, we propose a method for automatically detecting metaphors in texts to predict various mental health problems, specifically anxiety, depression, inferiority, sensitivity, social phobias,  ...  However, clinical diagnosis of mental health problems is costly, time-consuming, and often significantly delayed, which highlights the need for novel methods to identify them.  ...  We used a metaphor-based feature set and a sentiment-based feature set to build Metaphor-Sentiment Model (MSM) for predicting mental health status.  ... 
doi:10.1155/2021/5582714 pmid:34012545 pmcid:PMC8105119 fatcat:nwnq7avg3bco5cxaf4z3s4amgu

Linguistic features and psychological states: A machine-learning based approach

Xiaowei Du, Yunmei Sun
2022 Frontiers in Psychology  
Previous research mostly used simplistic measures and limited linguistic features (e.g., personal pronouns, absolutist words, and sentiment words) in a text to identify its author's psychological states  ...  In this study, we proposed using additional linguistic features, that is, sentiments polarities and emotions, to classify texts of various psychological states.  ... Du and Sun 10.3389/fpsyg.2022.955850  ... 
doi:10.3389/fpsyg.2022.955850 pmid:35936260 pmcid:PMC9355087 fatcat:giga3hhvvfcj5esvbqxa4rywvq

Analysis of sentiments on the onset of Covid-19 using Machine Learning Techniques

Vishakha Arya, Amit Kumar Mishra Mishra, Alfonso González-Briones
2022 Advances in Distributed Computing and Artificial Intelligence Journal  
With Natural Language Toolkit (NLTK), text classification for sentiment analysis and calculate the score subjective polarity, counts, and sentiment distribution.  ...  N-gram is used in textual mining -and Natural Language Processing for a continuous sequence of words in a text or document applying uni-gram, bi-gram, and tri-gram for statistical computation.  ...  Lexicon Valence Aware Dictionary and Sentiment Reasoner (VADER) included in the NLTK package is an unsupervised lexicon method and rule-based used to detect the sentiment of social media sites.  ... 
doi:10.14201/adcaij.27348 fatcat:rllmdx3v3jdbfbfmg7powjhyzy

Textual Sentiment Analysis using Machine Learning and NLP: A Review [chapter]

Neha Sharma, Department of CSE, RNTU, Bhopal, India, S Veenadhari, Rachna Kulhare
2021 New Frontiers in Communication and Intelligent Systems  
This paper directs towards creating a single framework in the future for depression and sentiment analysis.  ...  The objective of this paper is to analyze recently developed frameworks for the diagnosis of sentiment and depression level of an individual.  ...  [5] offered a united framework which bridges the gap between approaches of ML and lexicon-based for achieving better scalability and accuracy.  ... 
doi:10.52458/978-81-95502-00-4-51 fatcat:2tduezwf6bapvizb2u3rvpi2ja

Depressing-domain Lexicon Based on Microblogs: Automatic Construction (Preprint)

Genghao Li, Bing Li, Langlin Huang, Sibing Hou
2019 JMIR Medical Informatics  
During depression detection, we considered six features, and we used five classification methods to test the detection performance.  ...  These two methods combined performed well in a specific corpus during construction. The lexicon was obtained based on 111,052 Weibo microblogs from 1868 users who were depressed or nondepressed.  ...  This work was supported by the National Social Science Fund Project, China (No. 16BTQ065) "Multi-source intelligence fusion research on emergencies in big data environment" and the Foundation for Disciplinary  ... 
doi:10.2196/17650 pmid:32574151 fatcat:nhu32v6w2zh65lotqicl7refpm

Topic Model for Identifying Suicidal Ideation in Chinese Microblog

Xiaolei Huang, Xin Li, Tianli Liu, David Chiu, Tingshao Zhu, Lei Zhang
2015 Pacific Asia Conference on Language, Information and Computation  
Second, we build suicide psychological lexicon by psychological standards and word embedding technique.  ...  Furthermore, a prototype system for monitoring suicidal ideation on several social networks is deployed.  ...  For each microblog, we extracted both content related features and meta features (i.e., time, like, etc).  ... 
dblp:conf/paclic/HuangLLCZZ15 fatcat:npjgwd26ifec5fplqx6xymzmcq

Feature Based Depression Detection from Twitter Data Using Machine Learning Techniques

Piyush Kumar, Poulomi Samanta, Suchandra Dutta, Moumita Chatterjee, Dhrubasish Sarkar
2022 Journal of scientific research  
The work proposed a numerical score for each user based on the sentiment value of their tweets and demonstrated that this feature can detect depression with an accuracy of 78% with the XGBoost classifier  ...  According to the proposed research, proper feature selection and their combinations help in achieving better improvement in performance.  ...  score based on the sentiment value of their tweets. iv) We employed machine learning techniques for demonstrating the advantages of combining different features for achieving high performance in depression  ... 
doi:10.37398/jsr.2022.660229 fatcat:4b4xu32nafef5leldewjgsz2yi

Detection and Analysis of Stress using Machine Learning Techniques

2019 International Journal of Engineering and Advanced Technology  
Here using TensiStrengthframework for sentiment strength detection on social networking sites to extract sentiment strength from the informal English text.  ...  This classifies both positive and negative emotions based on the strength scale from -5 to +5 indications of sentiments.  ...  WSD improves the performance of lexicon based Stress/Relaxation detection algorithm TensiStrength. TensiStrength is a lexicon based sentiment analysis algorithm.  ... 
doi:10.35940/ijeat.f8573.109119 fatcat:qjqljdq3pnh5vfcmojixjyccee

A Multi-layered Psychological-Based Reference Model for Citizen Need Assessment Using AI-Powered Models

Rajwa Alharthi, Abdulmotaleb El Saddik
2020 SN Computer Science  
We evaluate the predictive powers of various textual, psychological, semantic, lexicon-based and Twitter-specific features.  ...  data collection, preprocessing, feature extraction and contextualization module.  ...  Score-Based Sentiment and Emotion Lexicons We used features derived from several sentiment and emotion-based lexicons.  ... 
doi:10.1007/s42979-020-00271-3 fatcat:o5qozqxr5jha7nmrsfl6xznrxe
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