Comparing selective masking methods for depression detection in social media (Record no. 19836)
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| fixed length control field | 240229s2022 th u m tt 000 a eng d |
| 035 ## - SYSTEM CONTROL NUMBER | |
| System control number | .b12421662 |
| 099 ## - LOCAL FREE-TEXT CALL NUMBER (OCLC) | |
| Classification number | AIT Thesis no.DSAI-22-04 |
| 100 0# - MAIN ENTRY--PERSONAL NAME | |
| Personal name | Chanapa Pananookooln |
| 245 10 - TITLE STATEMENT | |
| Title | Comparing selective masking methods for depression detection in social media |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. | |
| Place of publication, distribution, etc. | Pathum Thani, Thailand : |
| Name of publisher, distributor, etc. | Asian Institute of Technology, |
| Date of publication, distribution, etc. | 2022 |
| 300 ## - PHYSICAL DESCRIPTION | |
| Extent | 47 leaves : |
| Other physical details | ill. |
| 490 1# - SERIES STATEMENT | |
| Series statement | Thesis ; |
| Volume/sequential designation | no. DSAI-22-04 |
| 500 ## - GENERAL NOTE | |
| General note | A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science in Data Science and Artificial Intelligence, School of Engineering and Technology |
| 502 ## - DISSERTATION NOTE | |
| Dissertation note | Thesis (M. Sc.) - Asian Institute of Technology, 2022 |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc. | Identifying those at risk for depression is a crucial issue in which social media provides an excellent platform for examining the linguistic patterns of depressed individuals. A significant challenge in a depression classification problem is ensuring that the predic tion model is not overly dependent on keywords, such that it fails to predict when key words are unavailable. One promising approach is masking, i.e., by masking important words selectively and asking the model to predict the masked words, the model is forced to learn the context rather than the keywords. This study evaluates seven masking tech niques, such as random masking, log-odds ratio, and the use of attention scores. In ad dition, whether to predict the masked words during pretraining or fine-tuning phase was also examined. Last, six class imbalance ratios were compared to determine the robust ness of the masked selection methods. Key findings demonstrated that selective masking generally outperforms random masking in terms of classification accuracy. In addition, the most accurate and robust models were identified. Our research also indicated that re constructing the masked words during the pre-training phase is more advantageous than during the fine-tuning phase. Further discussion and implications were made. This is the first study to comprehensively compare masking selection methods, which has broad implications for the field of depression classification and the general NLP. Our code can be found in: https://github.com/chanapapan/Depression-Detection |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | Social media |
| General subdivision | Data processing |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | Machine learning |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | Neural networks (Computer science) |
| 700 0# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Chaklam Silpasuwanchai, |
| Relator term | Chairperson |
| 700 1# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Dailey, Matthew N., |
| Relator term | Examination Committee |
| 700 0# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Mongkol Ekpanyapong, |
| Relator term | Examination Committee |
| 710 2# - ADDED ENTRY--CORPORATE NAME | |
| Corporate name or jurisdiction name as entry element | His Majesty the King{u2019}s Scholarships (Thailand), |
| Relator term | Scholarship Donor |
| 810 2# - SERIES ADDED ENTRY--CORPORATE NAME | |
| Corporate name or jurisdiction name as entry element | Asian Institute of Technology. |
| Title of a work | Thesis ; |
| Volume/sequential designation | no. DSAI-22-04 |
| 856 40 - ELECTRONIC LOCATION AND ACCESS | |
| Materials specified | Full-Text |
| Uniform Resource Identifier | <a href="http://203.159.5.9/ait-thesis/Viewer/viewer.php?id=B20417">http://203.159.5.9/ait-thesis/Viewer/viewer.php?id=B20417</a> |
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| Withdrawn status | Lost status | Damaged status | Not for loan | Home library | Current library | Shelving location | Date acquired | Total checkouts | Full call number | Date last seen | Price effective from | Koha item type | Barcode | Copy number | Cost, normal purchase price |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Available for Loans | Asian Institute of Technology Library | Asian Institute of Technology Library | Archives | 17/08/2026 | AIT Thesis no.DSAI-22-04 | 17/08/2026 | 17/08/2026 | 67-Electronic Resource | |||||||
| Available for Loans | Asian Institute of Technology Library | Asian Institute of Technology Library | Archives | 17/08/2026 | AIT Thesis no.DSAI-22-04 | 17/08/2026 | 17/08/2026 | 40-Archives | 30050120899066 | 1 | |||||
| Available for Loans | Asian Institute of Technology Library | Asian Institute of Technology Library | AIT Publications | 17/08/2026 | AIT Thesis no.DSAI-22-04 | 17/08/2026 | 17/08/2026 | 20-AIT Publication | 30050120425151 | 1 | 50.00 | ||||
| Available for Loans | Asian Institute of Technology Library | Asian Institute of Technology Library | AIT Publications | 17/08/2026 | AIT Thesis no.DSAI-22-04 | 17/08/2026 | 17/08/2026 | 20-AIT Publication | 30050120425144 | 2 | 50.00 |

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