Proceedings ArticleDOI
Using textual data for Personality Prediction:A Machine Learning Approach
Aditi V. Kunte,Suja S. Panicker +1 more
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TLDR
Predicting personality with the help of data through social media is a promising approach as this method does not require any questionnaires to be filled by users thus reducing time and increasing credibility.Abstract:
Personality is an important parameter as it differentiates various individuals from one another. Personality prediction is an evergreen area of research. Predicting personality with the help of data through social media is a promising approach as this method does not require any questionnaires to be filled by users thus reducing time and increasing credibility. Thus having knowledge of personality is an interesting domain for researchers to work on. Predicting personality has many applications in real world. Use of social media is increasing day by day. Huge amount of textual data as well as images continue to explode to the web daily. Current work focuses on Linear Discriminate Analysis, Multinomial Naive Bayes and AdaBoost over Twitter standard dataset.read more
Citations
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Book ChapterDOI
Image Sentiment Analysis Using Deep Learning
Vipul Salunke,Suja S. Panicker +1 more
TL;DR: It is indicative that a combination of fast recurrent neural networks and CNN may produce high accuracy with minimum time complexity, as existing researchers reflect CNN provides around 96.50% average accuracy for sentiment classification on the flicker image dataset.
Journal Article
A Comprehensive Study on Social Network Mental Disorders Detection Via Online Social Media Mining
TL;DR: This paper aims to review some papers regarding research in sentiment analysis on Twitter, describing the methodologies adopted and models applied, along with describing a generalized Python based approach.
Proceedings ArticleDOI
Recommender System for Postpartum Depression Monitoring based on Sentiment Analysis
Marcilio B. Carneiro,Mario W. L. Moreira,Silas S. L. Pereira,Erica L. Gallindo,Joel J. P. C. Rodrigues +4 more
TL;DR: In this article, a context-aware solution based on text mining for gestational depression prevention is presented, which can be used as support to health professionals in monitoring high-risk pregnancies.
Journal ArticleDOI
Personality Modelling of Indonesian Twitter Users with XGBoost Based on the Five Factor Model
Journal ArticleDOI
The Performance of Personality-based Recommender System for Fashion with Demographic Data-based Personality Prediction
TL;DR: A new method to predict personality implicitly based on demographic data is proposed, based on findings by previous researchers stating that there is a correlation between demographic data and personality trait.
References
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Proceedings ArticleDOI
Social media user personality classification using computational linguistic
TL;DR: A simple application was developed based on the best statistical model compared before to classify an individual's personality with their Twitter username and gender as an input and shows the best performance in terms of speed in classifying the users.
Journal ArticleDOI
Detecting the dark side of personality using social media status updates
Reece Akhtar,Dave Winsborough,Uri Ort,Abigail Johnson,Tomas Chamorro-Premuzic,Tomas Chamorro-Premuzic +5 more
TL;DR: This article explored whether the "dark side" of personality (nonclinical dysfunctional dispositions) can be inferred through the language used in Facebook status updates and found that language use was found to hold a relationship with HDS scores.
Proceedings ArticleDOI
Sentiment Analysis of Marijuana Content via Facebook Emoji-Based Reactions
TL;DR: An emoji-based sentiment analysis and classifier to gain insights into users' emotional reactions to marijuana-related posts on Facebook revealed that "LIKE" and "LOVE" are the most frequently used reactions, and they are strongly correlated by a correlation coefficient of 0.82.
Proceedings ArticleDOI
Predicting Temperament from Twitter Data
TL;DR: This paper proposes a framework for temperament classification according to the theory of psychologist David Keirsey, and presents an accuracy higher than 70% for the Artisan and Guardian types.
Proceedings ArticleDOI
Wide Machine Learning Algorithms Evaluation Applied to ECG Authentication and Gender Recognition
TL;DR: Two independent experiments taking advantage of the ECG properties are performed about person authentication and gender recognition, with the best accuracy score over the 98% for ECG authentication and 94% for gender recognition.