| 21 |
Climate Change Sentiment Analysis Using Lexicon, Machine Learning and Hybrid Approaches
|
|
|
|
In: Sustainability; Volume 14; Issue 8; Pages: 4723 (2022)
|
|
BASE
|
|
Show details
|
|
|
| 22 |
Artificial Intelligent in Education
|
|
|
|
In: Sustainability; Volume 14; Issue 5; Pages: 2862 (2022)
|
|
BASE
|
|
Show details
|
|
|
| 23 |
eHealth Engagement on Facebook during COVID-19: Simplistic Computational Data Analysis
|
|
|
|
In: International Journal of Environmental Research and Public Health; Volume 19; Issue 8; Pages: 4615 (2022)
|
|
BASE
|
|
Show details
|
|
|
| 24 |
How Do Chinese People View Cyberbullying? A Text Analysis Based on Social Media
|
|
|
|
In: International Journal of Environmental Research and Public Health; Volume 19; Issue 3; Pages: 1822 (2022)
|
|
BASE
|
|
Show details
|
|
|
| 25 |
Knowledge Discovery from Large Amounts of Social Media Data
|
|
|
|
In: Applied Sciences; Volume 12; Issue 3; Pages: 1209 (2022)
|
|
BASE
|
|
Show details
|
|
|
| 26 |
Detecting Depression Signs on Social Media: A Systematic Literature Review
|
|
|
|
In: Healthcare; Volume 10; Issue 2; Pages: 291 (2022)
|
|
Abstract:
Among mental health diseases, depression is one of the most severe, as it often leads to suicide; due to this, it is important to identify and summarize existing evidence concerning depression sign detection research on social media using the data provided by users. This review examines aspects of primary studies exploring depression detection from social media submissions (from 2016 to mid-2021). The search for primary studies was conducted in five digital libraries: ACM Digital Library, IEEE Xplore Digital Library, SpringerLink, Science Direct, and PubMed, as well as on the search engine Google Scholar to broaden the results. Extracting and synthesizing the data from each paper was the main activity of this work. Thirty-four primary studies were analyzed and evaluated. Twitter was the most studied social media for depression sign detection. Word embedding was the most prominent linguistic feature extraction method. Support vector machine (SVM) was the most used machine-learning algorithm. Similarly, the most popular computing tool was from Python libraries. Finally, cross-validation (CV) was the most common statistical analysis method used to evaluate the results obtained. Using social media along with computing tools and classification methods contributes to current efforts in public healthcare to detect signs of depression from sources close to patients.
|
|
Keyword:
depression; sentiment analysis; social media
|
|
URL: https://doi.org/10.3390/healthcare10020291
|
|
BASE
|
|
Hide details
|
|
|
| 27 |
A Novel Method of Generating Geospatial Intelligence from Social Media Posts of Political Leaders
|
|
|
|
In: Information; Volume 13; Issue 3; Pages: 120 (2022)
|
|
BASE
|
|
Show details
|
|
|
| 28 |
Vedantic Basis and Praxis of the Integral Advaita of Sri Aurobindo
|
|
|
|
In: Monsoon: South Asian Studies Association Journal (2022)
|
|
BASE
|
|
Show details
|
|
|
| 29 |
Tusha Hiti: The Origin and Significance of the Name
|
|
|
|
In: Monsoon: South Asian Studies Association Journal (2022)
|
|
BASE
|
|
Show details
|
|
|
| 30 |
Diversity, Equity, and Inclusion: Perspectives from Contemporary India and 6th Century Jain Yoga
|
|
|
|
In: Monsoon: South Asian Studies Association Journal (2022)
|
|
BASE
|
|
Show details
|
|
|
| 31 |
Ganges in Indian Sculpture and Literature: Mythology and Personification
|
|
|
|
In: Monsoon: South Asian Studies Association Journal (2022)
|
|
BASE
|
|
Show details
|
|
|
| 32 |
Digital and Spatial Humanities Mapping: Eurasia-Pacific Early Trade and Belief Linkages
|
|
|
|
In: Monsoon: South Asian Studies Association Journal (2022)
|
|
BASE
|
|
Show details
|
|
|
| 33 |
Overview of GermEval Task 2, 2019 shared task on the identification of offensive language
|
|
|
|
BASE
|
|
Show details
|
|
|
| 34 |
Using social media and personality traits to assess software developers' emotions ...
|
|
|
|
BASE
|
|
Show details
|
|
|
| 35 |
Using social media and personality traits to assess software developers' emotions ...
|
|
|
|
BASE
|
|
Show details
|
|
|
| 36 |
Exploring the Effects of Linguistic Elements of Social Media Corporate Apologies on Consumer Responses
|
|
|
|
In: Association of Marketing Theory and Practice Proceedings 2022 (2022)
|
|
BASE
|
|
Show details
|
|
|
| 37 |
The “Social” in Social VR: A Linguistic Analysis of Verbal Behavior in Groups ...
|
|
|
|
BASE
|
|
Show details
|
|
|
|
|
