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Sentiment analysis on educational posts from social media

Published: 11 January 2018 Publication History

Abstract

Social Networking on social media websites involves the use of the internet to connect users with their friends, family and acquaintances. Due to the increasing influence of social media such as Twitter, more number of users participates in the discussion and different users belong to different kind of groups. Positive, negative, and neutral comments are posted by the user and they participate in the discussion. The study mainly focused on the educational posts gathered from the Twitter social media. The web analytics technique was used in gathering and analyzing insights into community actions and attitudes through data collection, pre-processing, classification, and analysis of results. The collected tweets from February 1, 2017 to March 30, 2017 were 1,717 using the keywords Philippine education, DepEd K-12 and CHED K-12. After cleaning, 1,548 tweets were derived and classified as positive, negative, and neutral with 74.9% accuracy evaluation level. Results showed that mostly had expressed their negativity on the implementation of the K-12 program in the country. Measures such as hiring of teachers, sufficient allocation and utilization of funds for the procurement of books and resources, and sending the teachers concerned for training is deemed necessary to address the sentiments of the people. It is recommended then that an in-depth study of the K-12 implementation may be conducted to further improve the Philippine educational system. Results may also be presented to the officials of DepEd for validation and consideration to further enhance the implementation of K-12 program, as the next step of the study.

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Cited By

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  • (2024)Mining Social Media for Data-Driven Analysis of Educational Data with Machine Learning2024 4th International Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME)10.1109/ICECCME62383.2024.10796864(1-6)Online publication date: 4-Nov-2024
  • (2023)Sentiment Analysis on Educational Tweets: A Case of National Education Policy 20202023 IEEE International Conference on Contemporary Computing and Communications (InC4)10.1109/InC457730.2023.10262944(1-6)Online publication date: 21-Apr-2023
  • (2023)Translator Data Pre-processing Gram Feature Algorithmic Model (TDGA) for Enhancing Classifier Accuracy in the Healthcare DomainSN Computer Science10.1007/s42979-023-01895-x4:5Online publication date: 29-Jul-2023
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  1. Sentiment analysis on educational posts from social media

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    cover image ACM Other conferences
    IC4E '18: Proceedings of the 9th International Conference on E-Education, E-Business, E-Management and E-Learning
    January 2018
    128 pages
    ISBN:9781450354851
    DOI:10.1145/3183586
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 11 January 2018

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    Author Tags

    1. K-12 program
    2. Twitter
    3. educational post
    4. sentiment analysis
    5. social media

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    View all
    • (2024)Mining Social Media for Data-Driven Analysis of Educational Data with Machine Learning2024 4th International Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME)10.1109/ICECCME62383.2024.10796864(1-6)Online publication date: 4-Nov-2024
    • (2023)Sentiment Analysis on Educational Tweets: A Case of National Education Policy 20202023 IEEE International Conference on Contemporary Computing and Communications (InC4)10.1109/InC457730.2023.10262944(1-6)Online publication date: 21-Apr-2023
    • (2023)Translator Data Pre-processing Gram Feature Algorithmic Model (TDGA) for Enhancing Classifier Accuracy in the Healthcare DomainSN Computer Science10.1007/s42979-023-01895-x4:5Online publication date: 29-Jul-2023
    • (2023)Analysis of the Lingering Effects of Covid-19 on Distance EducationArtificial Intelligence Applications and Innovations10.1007/978-3-031-34111-3_17(189-200)Online publication date: 1-Jun-2023
    • (2022)An Initial Exploration of Tweets Associated With Web AccessibilityInternational Journal of Art, Culture, Design, and Technology10.4018/IJACDT.31284811:1(1-22)Online publication date: 25-Oct-2022
    • (2022)Gifted Education on Reddit: A Social Media Sentiment AnalysisGifted Child Quarterly10.1177/0016986222107640366:4(296-315)Online publication date: 9-Feb-2022
    • (2021)Sentiment Analysis and Topic Modeling on Tweets about Online Education during COVID-19Applied Sciences10.3390/app1118843811:18(8438)Online publication date: 12-Sep-2021
    • (2020)Twitter Data Collection and ExtractionProceedings of the 2020 the 4th International Conference on Information System and Data Mining10.1145/3404663.3404686(71-76)Online publication date: 15-May-2020
    • (2019)A Content Analysis System That Supports Sentiment Analysis for Subjectivity and Polarity Detection in Online CoursesIEEE Revista Iberoamericana de Tecnologias del Aprendizaje10.1109/RITA.2019.295229814:4(177-187)Online publication date: Nov-2019
    • (2019)Full Consideration of Big Data Characteristics in Sentiment Analysis Context2019 IEEE 4th International Conference on Cloud Computing and Big Data Analysis (ICCCBDA)10.1109/ICCCBDA.2019.8725728(126-130)Online publication date: Apr-2019

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