Text Mining Analysis of Comments in Thai Language for Depression from Online Social Networks

Chaiwuttisak, Pornpimol

doi:10.1007/978-3-030-49536-7_26

Cited by 2 publications

(1 citation statement)

References 4 publications

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“…This requires proper preprocessing of the acquired text (tokenizing, removal of stop words, stemming, and case transformation). The TF-IDF method, being the most widely used method [60] in the literature, was used to identify the most frequently used terms and according to [61], Fp-tree algorithm offered good results for extracting association rules from text. Therefore, in this work we used the TF-IDF method (one gram) to extract frequently occurring terms from DT definitions and used Fp trees to extract association DT elements.…”

Section: Phase Three: Extracting Major Dt Elements (Using Textmentioning

confidence: 99%

Consolidated Definition of Digital Transformation by using Text Mining

H¹,

ElKadi²,

El-Tazi³

2023

IJACSA

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Digital transformation has become essential for the majority of organizations, in both public and private sectors. The term "digital transformation" has been used (and misused), so frequently that it is now somewhat ambiguous. It has become imperative to give it some conceptual rigor. The objective of this study is to identify the major elements of digital transformation as well as develop a proper definition for DT in the public and private sectors. For this purpose, 56 different definitions of DT collected from the available literature were analyzed, and we found that they extracted elements from definition of DT manually. So, text mining (TF-IDF and Fp-tree) techniques are used to identify the major constituents and finally consolidate in generic DT definitions. The approach consists of five phases: 1) collecting and classifying DT definitions; 2) detecting synonyms; 3) extracting major elements (terms); 4) discussing and comparing DT elements; 5) formulating DT definitions for different business categories. An evaluation tool was also developed to assess the level of DT elements coverage in various definitions found in the literature, and, as a validation, it was applied to the formulated definitions.

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Section: Phase Three: Extracting Major Dt Elements (Using Textmentioning

confidence: 99%

Consolidated Definition of Digital Transformation by using Text Mining

H¹,

ElKadi²,

El-Tazi³

2023

IJACSA

View full text Add to dashboard Cite

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Depression Detection Model in Social Network Content

Rabie

Hashem

Alsheref

2022

International Journal of Software Innovation

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Social media (SM) is a platform that generates a massive quantity of data every day and allows individuals to engage with one another. For many people, social media has evolved into a way of life and the fifth component of daily living. Among the most popular social media platforms are Facebook, Instagram, Twitter, WhatsApp, and Snapchat. Depression is a frequent and dangerous medical condition that has a negative impact on how you feel, think, and act. A therapist's ability to swiftly detect depression in persons is limited since they cannot observe a person's mood throughout the day. Researchers can assess a person's sentiments via social media by looking at the user's posts and comments to discover if he or she has a mental issue. This survey study mirrors prior research on detecting depression using user-generated material from social media platforms, which introduce different techniques and compare between it to obtain accuracy.

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Text Mining Analysis of Comments in Thai Language for Depression from Online Social Networks

Cited by 2 publications

References 4 publications

Consolidated Definition of Digital Transformation by using Text Mining

Consolidated Definition of Digital Transformation by using Text Mining

Depression Detection Model in Social Network Content

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