Proceedings ArticleDOI
Using textual data for Personality Prediction:A Machine Learning Approach
Aditi V. Kunte,Suja S. Panicker +1 more
Reads0
Chats0
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
More filters
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
More filters
Journal ArticleDOI
Predicting Microblog Sentiments via Weakly Supervised Multimodal Deep Learning
TL;DR: A weakly supervised multimodal deep learning scheme toward robust and scalable sentiment prediction that learns convolutional neural networks iteratively and selectively from “weak” emoticon labels, which are cheaply available and noise containing.
Journal ArticleDOI
A holistic system for troll detection on Twitter
TL;DR: TrollPacifier is described, a holistic system for troll detection, which analyses many different features of trolls and legitimate users on the popular Twitter platform and demonstrates that automatic classification can be useful in the whole process of identification and management of online anti-social behaviors.
Journal ArticleDOI
A Comprehensive Study on Social Network Mental Disorders Detection via Online Social Media Mining
Hong-Han Shuai,Chih-Ya Shen,De-Nian Yang,Yi-Feng Carol Lan,Wang-Chien Lee,Philip S. Yu,Ming-Syan Chen +6 more
TL;DR: This paper proposes a machine learning framework, namely, Social Network Mental Disorder Detection (SNMDD), that exploits features extracted from social network data to accurately identify potential cases of SNMDs and proposes a new SNMD-based Tensor Model (STM) to improve the accuracy.
Proceedings ArticleDOI
T-PICE: Twitter Personality Based Influential Communities Extraction System
TL;DR: This work describes the Twitter Personality based Influential Communities Extraction (T-PICE) system, a system that creates the best influential communities in a Twitter network graph considering users' personality, and defines several metrics to count the influence of communities.
Proceedings ArticleDOI
Predicting facebook-users' personality based on status and linguistic features via flexible regression analysis techniques
TL;DR: This paper explores the use of Linear Regression and Support Vector Regression for predicting the Big Five Personality scores, which provide a quantitative measure of the personality traits of users and finds that SVR with Polynomial and Radial Basis Function kernel, respectively, provides better results in predicting big five personality traits.