{"id":62374,"date":"2025-04-09T14:19:05","date_gmt":"2025-04-09T14:19:05","guid":{"rendered":""},"modified":"2025-04-09T14:19:05","modified_gmt":"2025-04-09T14:19:05","slug":"%d8%aa%d8%b1%d8%ac%d9%85%d9%87-%d9%81%d8%a7%d8%b1%d8%b3%db%8c-%d9%85%d9%82%d8%a7%d9%84%d9%87-62374","status":"publish","type":"product","link":"https:\/\/express24.ir\/d\/product\/%d8%aa%d8%b1%d8%ac%d9%85%d9%87-%d9%81%d8%a7%d8%b1%d8%b3%db%8c-%d9%85%d9%82%d8%a7%d9%84%d9%87-62374\/","title":{"rendered":"\u062a\u0631\u062c\u0645\u0647 \u0641\u0627\u0631\u0633\u06cc \u0645\u0642\u0627\u0644\u0647 \u062a\u0628\u062f\u06cc\u0644 \u0632\u0628\u0627\u0644\u0647 \u0628\u0647 \u06af\u0646\u062c: \u062a\u0633\u0631\u06cc\u0639 \u0627\u0633\u062a\u0646\u062a\u0627\u062c \u0645\u062f\u0644\u200c\u0647\u0627\u06cc \u0632\u0628\u0627\u0646 \u0628\u0632\u0631\u06af \u0628\u0627 \u0628\u0627\u0632\u06cc\u0627\u0641\u062a \u062a\u0648\u06a9\u0646"},"content":{"rendered":"\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
\u0639\u0646\u0648\u0627\u0646 \u0645\u0642\u0627\u0644\u0647 \u0628\u0647 \u0627\u0646\u06af\u0644\u06cc\u0633\u06cc <\/td>\nQuantifying the Effectiveness of Student Organization Activities using Natural Language Processing<\/td>\n<\/tr>\n
\u0639\u0646\u0648\u0627\u0646 \u0645\u0642\u0627\u0644\u0647 \u0628\u0647 \u0641\u0627\u0631\u0633\u06cc <\/td>\n\u062a\u0631\u062c\u0645\u0647 \u0641\u0627\u0631\u0633\u06cc \u0645\u0642\u0627\u0644\u0647 \u062a\u0628\u062f\u06cc\u0644 \u0632\u0628\u0627\u0644\u0647 \u0628\u0647 \u06af\u0646\u062c: \u062a\u0633\u0631\u06cc\u0639 \u0627\u0633\u062a\u0646\u062a\u0627\u062c \u0645\u062f\u0644\u200c\u0647\u0627\u06cc \u0632\u0628\u0627\u0646 \u0628\u0632\u0631\u06af \u0628\u0627 \u0628\u0627\u0632\u06cc\u0627\u0641\u062a \u062a\u0648\u06a9\u0646<\/td>\n<\/tr>\n
\u0646\u0648\u06cc\u0633\u0646\u062f\u06af\u0627\u0646 <\/td>\nLyberius Ennio F. Taruc, Arvin R. De La Cruz<\/td>\n<\/tr>\n
\u0641\u0631\u0645\u062a \u0645\u0642\u0627\u0644\u0647 \u0627\u0646\u06af\u0644\u06cc\u0633\u06cc <\/td>\nPDF<\/td>\n<\/tr>\n
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\u062a\u0639\u062f\u0627\u062f \u0635\u0641\u062d\u0627\u062a<\/td>\n11<\/td>\n<\/tr>\n
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\u062f\u0633\u062a\u0647 \u0628\u0646\u062f\u06cc \u0645\u0648\u0636\u0648\u0639\u0627\u062a <\/td>\nComputation and Language,Artificial Intelligence,Emerging Technologies,\u0645\u062d\u0627\u0633\u0628\u0627\u062a \u0648 \u0632\u0628\u0627\u0646 , \u0647\u0648\u0634 \u0645\u0635\u0646\u0648\u0639\u06cc , \u0641\u0646 \u0622\u0648\u0631\u06cc \u0647\u0627\u06cc \u0646\u0648\u0638\u0647\u0648\u0631 ,<\/td>\n<\/tr>\n
\u062a\u0648\u0636\u06cc\u062d\u0627\u062a <\/td>\nSubmitted 16 August, 2024; originally announced August 2024. , Comments: 11 pages, 4 figures, presented in International Conference on Generative Al and its Applications (ICGAIA-24) last 22nd – 23rd, July, 2024 at Jakarta, Indonesia , Journal ref: IJISAE, 2024, 12(22s), 1553-1563<\/td>\n<\/tr>\n
\u062a\u0648\u0636\u06cc\u062d\u0627\u062a \u0628\u0647 \u0641\u0627\u0631\u0633\u06cc <\/td>\n\u0627\u0631\u0627\u0626\u0647 \u0634\u062f\u0647 16 \u0627\u0648\u062a 2024 \u061b\u062f\u0631 \u0627\u0628\u062a\u062f\u0627 \u0627\u0648\u062a 2024. \u060c \u0646\u0638\u0631\u0627\u062a: 11 \u0635\u0641\u062d\u0647 \u060c 4 \u0631\u0642\u0645 \u060c \u062f\u0631 \u06a9\u0646\u0641\u0631\u0627\u0646\u0633 \u0628\u06cc\u0646 \u0627\u0644\u0645\u0644\u0644\u06cc \u062a\u0648\u0644\u06cc\u062f \u06a9\u0646\u0646\u062f\u0647 AL \u0648 \u0628\u0631\u0646\u0627\u0645\u0647 \u0647\u0627\u06cc \u0622\u0646 (ICGAIA -24) 22 – 23 \u060c \u0698\u0648\u0626\u06cc\u0647 \u060c 2024 \u062f\u0631 \u062c\u0627\u06a9\u0627\u0631\u062a\u0627 \u060c \u0627\u0646\u062f\u0648\u0646\u0632\u06cc \u060c \u0645\u062c\u0644\u0647 Ref: Ijisae \u060c 2024 \u060c 12(22s) \u060c 1553-1563<\/td>\n<\/tr>\n
\u0627\u0637\u0644\u0627\u0639\u0627\u062a \u0628\u06cc\u0634\u062a\u0631 \u0627\u0632 \u0627\u06cc\u0646 \u0645\u0642\u0627\u0644\u0647 \u062f\u0631 \u067e\u0627\u06cc\u06af\u0627\u0647 \u0647\u0627\u06cc \u0639\u0644\u0645\u06cc <\/td>\n\n INSPIRE HEP<\/a>
\n
\n NASA ADS<\/a>
\n
\n Google Scholar<\/a>
\n
\n Semantic Scholar<\/a>
\n
\n arXiv<\/a><\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n\r\n\r\n \r\n \r\n \r\n \r\n
\u0641\u0631\u0645\u062a \u0627\u0631\u0627\u0626\u0647 \u062a\u0631\u062c\u0645\u0647 \u0645\u0642\u0627\u0644\u0647 <\/td>\r\n \u062a\u062d\u0648\u06cc\u0644 \u0628\u0647 \u0635\u0648\u0631\u062a \u0641\u0627\u06cc\u0644 \u0648\u0631\u062f<\/td>\r\n <\/tr>\r\n
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\u062c\u062f\u0627\u0648\u0644 \u0648 \u0641\u0631\u0645\u0648\u0644 \u0647\u0627 <\/td>\r\n \u06a9\u0644\u06cc\u0647 \u062c\u062f\u0627\u0648\u0644 \u0648 \u0641\u0631\u0645\u0648\u0644 \u0647\u0627 \u0646\u06cc\u0632 \u062f\u0631 \u0641\u0627\u06cc\u0644 \u062a\u062d\u0648\u06cc\u0644\u06cc \u0648\u0631\u062f \u062f\u0631\u062c \u0645\u06cc\u200c\u0634\u0648\u0646\u062f.<\/td>\r\n <\/tr>\r\n<\/table>\r\n\r\n\n

\u0686\u06a9\u06cc\u062f\u0647<\/h2>\n

Student extracurricular activities play an important role in enriching the students’ educational experiences. With the increasing popularity of Machine Learning and Natural Language Processing, it becomes a logical step that incorporating ML-NLP in improving extracurricular activities is a potential focus of study in Artificial Intelligence (AI). This research study aims to develop a machine learning workflow that will quantify the effectiveness of student-organized activities based on student emotional responses using sentiment analysis. The study uses the Bidirectional Encoder Representations from Transformers (BERT) Large Language Model (LLM) called via the pysentimiento toolkit, as a Transformer pipeline in Hugging Face. A sample data set from Organization C, a Recognized Student Organization (RSO) of a higher educational institute in the Philippines, College X, was used to develop the workflow. The workflow consisted of data preprocessing, key feature selection, LLM feature processing, and score aggregation, resulting in an Event Score for each data set. The results show that the BERT LLM can also be used effectively in analyzing sentiment beyond product reviews and post comments. For the student affairs offices of educational institutions, this study can provide a practical example of how NLP can be applied to real-world scenarios, showcasing the potential impact of data-driven decision making.<\/p>\n

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\u062a\u0631\u0627\u0646\u0633\u0641\u0648\u0631\u0645\u0627\u062a\u0648\u0631 \u062f\u0631 \u0628\u063a\u0644 \u06a9\u0631\u062f\u0646 \u0635\u0648\u0631\u062a \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0645\u06cc \u06a9\u0646\u062f.\u0627\u0632 \u062f\u0627\u062f\u0647 \u0647\u0627\u06cc \u0646\u0645\u0648\u0646\u0647 \u0627\u06cc \u0627\u0632 \u0633\u0627\u0632\u0645\u0627\u0646 C \u060c \u06cc\u06a9 \u0633\u0627\u0632\u0645\u0627\u0646 \u062f\u0627\u0646\u0634\u062c\u0648\u06cc\u06cc \u0634\u0646\u0627\u062e\u062a\u0647 \u0634\u062f\u0647 (RSO) \u0627\u0632 \u06cc\u06a9 \u0645\u0648\u0633\u0633\u0647 \u0622\u0645\u0648\u0632\u0634\u06cc \u0639\u0627\u0644\u06cc \u062f\u0631 \u0641\u06cc\u0644\u06cc\u067e\u06cc\u0646 \u060c \u06a9\u0627\u0644\u062c X \u060c \u0628\u0631\u0627\u06cc \u062a\u0648\u0633\u0639\u0647 \u06af\u0631\u062f\u0634 \u06a9\u0627\u0631 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0634\u062f.\u06af\u0631\u062f\u0634 \u06a9\u0627\u0631 \u0634\u0627\u0645\u0644 \u067e\u06cc\u0634 \u067e\u0631\u062f\u0627\u0632\u0634 \u062f\u0627\u062f\u0647 \u0647\u0627 \u060c \u0627\u0646\u062a\u062e\u0627\u0628 \u0648\u06cc\u0698\u06af\u06cc \u0647\u0627\u06cc \u06a9\u0644\u06cc\u062f\u06cc \u060c \u067e\u0631\u062f\u0627\u0632\u0634 \u0648\u06cc\u0698\u06af\u06cc \u0647\u0627\u06cc LLM \u0648 \u062a\u062c\u0645\u0639 \u0646\u0645\u0631\u0647 \u0628\u0648\u062f \u0648 \u062f\u0631 \u0646\u062a\u06cc\u062c\u0647 \u0646\u0645\u0631\u0647 \u0631\u0648\u06cc\u062f\u0627\u062f \u0628\u0631\u0627\u06cc \u0647\u0631 \u0645\u062c\u0645\u0648\u0639\u0647 \u062f\u0627\u062f\u0647 \u0627\u06cc\u062c\u0627\u062f \u0645\u06cc \u0634\u0648\u062f.\u0646\u062a\u0627\u06cc\u062c \u0646\u0634\u0627\u0646 \u0645\u06cc \u062f\u0647\u062f \u06a9\u0647 BERT LLM \u0647\u0645\u0686\u0646\u06cc\u0646 \u0645\u06cc \u062a\u0648\u0627\u0646\u062f \u0628\u0647 \u0637\u0648\u0631 \u0645\u0624\u062b\u0631 \u062f\u0631 \u062a\u062c\u0632\u06cc\u0647 \u0648 \u062a\u062d\u0644\u06cc\u0644 \u0627\u062d\u0633\u0627\u0633\u0627\u062a \u0641\u0631\u0627\u062a\u0631 \u0627\u0632 \u0628\u0631\u0631\u0633\u06cc \u0645\u062d\u0635\u0648\u0644 \u0648 \u0627\u0631\u0633\u0627\u0644 \u0646\u0638\u0631\u0627\u062a \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0634\u0648\u062f.\u0628\u0631\u0627\u06cc \u062f\u0641\u0627\u062a\u0631 \u0627\u0645\u0648\u0631 \u062f\u0627\u0646\u0634\u062c\u0648\u06cc\u06cc \u0645\u0624\u0633\u0633\u0627\u062a \u0622\u0645\u0648\u0632\u0634\u06cc \u060c \u0627\u06cc\u0646 \u0645\u0637\u0627\u0644\u0639\u0647 \u0645\u06cc \u062a\u0648\u0627\u0646\u062f \u0646\u0645\u0648\u0646\u0647 \u0627\u06cc \u0639\u0645\u0644\u06cc \u0627\u0632 \u0646\u062d\u0648\u0647 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 NLP \u062f\u0631 \u0633\u0646\u0627\u0631\u06cc\u0648\u0647\u0627\u06cc \u062f\u0646\u06cc\u0627\u06cc \u0648\u0627\u0642\u0639\u06cc \u0631\u0627 \u0627\u0631\u0627\u0626\u0647 \u062f\u0647\u062f \u060c \u0648 \u062a\u0623\u062b\u06cc\u0631 \u0628\u0627\u0644\u0642\u0648\u0647 \u062a\u0635\u0645\u06cc\u0645 \u06af\u06cc\u0631\u06cc \u0645\u0628\u062a\u0646\u06cc \u0628\u0631 \u062f\u0627\u062f\u0647 \u0631\u0627 \u0646\u0634\u0627\u0646 \u0645\u06cc \u062f\u0647\u062f.<\/p>\n\r\n\r\n \r\n \r\n \r\n \r\n
\u0641\u0631\u0645\u062a \u0627\u0631\u0627\u0626\u0647 \u062a\u0631\u062c\u0645\u0647 \u0645\u0642\u0627\u0644\u0647 <\/td>\r\n \u062a\u062d\u0648\u06cc\u0644 \u0628\u0647 \u0635\u0648\u0631\u062a \u0641\u0627\u06cc\u0644 \u0648\u0631\u062f<\/td>\r\n <\/tr>\r\n
\u0632\u0645\u0627\u0646 \u062a\u062d\u0648\u06cc\u0644 \u062a\u0631\u062c\u0645\u0647 \u0645\u0642\u0627\u0644\u0647 <\/td>\r\n \u0628\u06cc\u0646 2 \u062a\u0627 3 \u0631\u0648\u0632 \u067e\u0633 \u0627\u0632 \u062b\u0628\u062a \u0633\u0641\u0627\u0631\u0634<\/td>\r\n <\/tr>\r\n\t
\u06a9\u06cc\u0641\u06cc\u062a \u062a\u0631\u062c\u0645\u0647 <\/td>\r\n \u0628\u0633\u06cc\u0627\u0631 \u0628\u0627\u0644\u0627. \u0645\u0642\u0627\u0644\u0647 \u0641\u0642\u0637 \u062a\u0648\u0633\u0637 \u0645\u062a\u0631\u062c\u0645\u06cc\u0646 \u0628\u0627 \u0645\u062f\u0631\u06a9 \u062f\u0627\u0646\u0634\u06af\u0627\u0647\u06cc \u0645\u062a\u0631\u062c\u0645\u06cc \u062a\u0631\u062c\u0645\u0647 \u0645\u06cc\u200c\u0634\u0648\u062f.<\/td>\r\n <\/tr>\r\n\t\t
\u062c\u062f\u0627\u0648\u0644 \u0648 \u0641\u0631\u0645\u0648\u0644 \u0647\u0627 <\/td>\r\n \u06a9\u0644\u06cc\u0647 \u062c\u062f\u0627\u0648\u0644 \u0648 \u0641\u0631\u0645\u0648\u0644 \u0647\u0627 \u0646\u06cc\u0632 \u062f\u0631 \u0641\u0627\u06cc\u0644 \u062a\u062d\u0648\u06cc\u0644\u06cc \u0648\u0631\u062f \u062f\u0631\u062c \u0645\u06cc\u200c\u0634\u0648\u0646\u062f.<\/td>\r\n <\/tr>\r\n<\/table>\r\n\r\n\n","protected":false},"excerpt":{"rendered":"

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