AIMC Topic: Blogging

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A deep learning model for detecting mental illness from user content on social media.

Scientific reports Jul 16, 2020
Users of social media often share their feelings or emotional states through their posts. In this study, we developed a deep learning model to identify a user's mental state based on his/her posting information. To this end, we collected posts from m...
Humans Female Adult Mental Health Male Anxiety Deep Learning Depression Bipolar Disorder Social Media Schizophrenia Semantics Autistic Disorder Phonetics Borderline Personality Disorder Blogging Psycholinguistics
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Analyzing depression tendency of web posts using an event-driven depression tendency warning model.

Artificial intelligence in medicine Nov 2, 2015
OBJECTIVE: The Internet has become a platform to express individual moods/feelings of daily life, where authors share their thoughts in web blogs, micro-blogs, forums, bulletin board systems or other media. In this work, we investigate text-mining te...
Humans Risk Factors Risk Assessment Depressive Disorder, Major Diagnosis, Computer-Assisted Emotions Predictive Value of Tests Natural Language Processing Data Mining Early Diagnosis Pattern Recognition, Automated Vocabulary Blogging
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Using support vector machine ensembles for target audience classification on Twitter.

PloS one Apr 13, 2015
The vast amount and diversity of the content shared on social media can pose a challenge for any business wanting to use it to identify potential customers. In this paper, our aim is to investigate the use of both unsupervised and supervised learning...
Humans Support Vector Machine Social Media Data Mining Blogging Marketing
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