Implementation of SVM, k-NN, and DT for Toxicity and Sentiment Classification of AWA Vlog Content in Wasur National Park

 (*)Yerik Afrianto Singgalen Mail (Atma Jaya Catholic University of Indonesia, Jakarta, Indonesia)

(*) Corresponding Author

Submitted: January 30, 2024; Published: April 30, 2024


This study delves into the response of viewers to video content focusing on Wasur National Park in Papua, Indonesia, with a particular emphasis on its implications for livelihood and ecology. The increasing popularity of online platforms such as YouTube has provided a medium for content creators to showcase natural landscapes and cultural heritage, potentially influencing viewers' perceptions and behaviors toward conservation efforts. Employing the CRISP-DM (Cross-Industry Standard Process for Data Mining) framework, this research systematically analyzes a specific video from the AWA channel, known for its documentaries on environmental and cultural topics. The methodology involves sentiment analysis to gauge viewers' emotional responses, toxicity assessment to identify harmful content, and thematic coding to categorize comments based on recurring themes. The analysis reveals that viewers engage with the content positively, expressing appreciation for the video's educational and visually compelling nature. Moreover, the study identifies various dimensions of toxicity within the dataset, including Toxicity (0.05364), Severe Toxicity (0.00629), Identity Attack (0.02250), Insult (0.03534), Profanity (0.03589), and Threat (0.01280). Furthermore, the performance of the Support Vector Machine (SVM) with Synthetic Minority Over-sampling Technique (SMOTE) is highlighted, demonstrating its effectiveness in classifying sentiment with an accuracy of 93.86%, precision of 100.00%, recall of 87.73%, f-measure of 93.44%, and an Area Under the Curve (AUC) value of 1.000. This research underscores the significance of balanced media portrayals in fostering positive attitudes toward environmental conservation and cultural preservation.


SVM; k-NN; DT; National Park; Wasur

Full Text:


Article Metrics

Abstract view : 104 times
PDF - 25 times


N. Kusumastuti, Suratman, and A. Pitoyo, “Orchids diversity on six forest types in Wasur National Park, Merauke, Papua, Indonesia,” Asian J. For., vol. 5, no. 2, pp. 101–110, 2021, doi: 10.13057/asianjfor/r050206.

I. C. A. Phoek, A. P. Tjilen, and E. Cahyono, “Analysis of Ecotourism, Culture and Local Community Empowerment: Case Study of Wasur National Park - Indonesia,” Macro Manag. Public Policies, vol. 3, no. 2, pp. 7–13, 2021, doi: 10.30564/mmpp.v3i2.3414.

S. W. Ririhena, A. Phuk Tjilen, E. Cahyono, and I. Cara Alexander Phoek, “Factors influencing ecotourism in Wasur national park Merauke regency,” Int. J. Hosp. Tour. Stud., vol. 1, no. 2, pp. 119–126, 2020, doi: 10.31559/ijhts2020.1.2.5.

I. Moyo and H. M. S. Cele, “Protected areas and environmental conservation in KwaZulu-Natal, South Africa: on HEIs, livelihoods and sustainable development,” Int. J. Sustain. High. Educ., vol. 22, no. 7, pp. 1536–1551, Jan. 2021, doi: 10.1108/IJSHE-05-2020-0157.

M. Dell’Eva, C. R. Nava, and L. Osti, “Perceptions and satisfaction of human–animal encounters in protected areas,” Worldw. Hosp. Tour. Themes, vol. 12, no. 4, pp. 441–458, Jan. 2020, doi: 10.1108/WHATT-05-2020-0024.

W. C. Rop, “Modelling the impact of geo-tourism on geo-conservation of Hell’s Gate National Park in Kenya,” Ecofeminism Clim. Chang., vol. 2, no. 1, pp. 17–25, Jan. 2021, doi: 10.1108/efcc-05-2020-0015.

Y. Yu, D. T. Dinh, B. H. Nguyen, F. Yu, and V. N. Huynh, “Mining Insights From Esports Game Reviews With an Aspect-Based Sentiment Analysis Framework,” IEEE Access, vol. 11, no. June, pp. 61161–61172, 2023, doi: 10.1109/ACCESS.2023.3285864.

U. Sehar, S. Kanwal, K. Dashtipur, U. Mir, U. Abbasi, and F. Khan, “Urdu Sentiment Analysis via Multimodal Data Mining Based on Deep Learning Algorithms,” IEEE Access, vol. 9, pp. 153072–153082, 2021, doi: 10.1109/ACCESS.2021.3122025.

Y. Zhang, C. Zhu, and Y. Xie, “Fine-Grained Sentiment Analysis of Cross-Domain Chinese E-Commerce Texts Based on SKEP-Gram-CDNN,” IEEE Access, vol. 11, no. July, pp. 74058–74070, 2023, doi: 10.1109/ACCESS.2023.3296447.

K. Jahanbin and M. A. Z. Chahooki, “Aspect-Based Sentiment Analysis of Twitter Influencers to Predict the Trend of Cryptocurrencies Based on Hybrid Deep Transfer Learning Models,” IEEE Access, vol. 11, no. November, pp. 121656–121670, 2023, doi: 10.1109/ACCESS.2023.3327060.

J. Zhou, S. Jin, and X. Huang, “ADeCNN: An improved model for aspect-level sentiment analysis based on deformable CNN and attention,” IEEE Access, vol. 8, pp. 132970–132979, 2020, doi: 10.1109/ACCESS.2020.3010802.

Y. A. Singgalen, “Social Network Analysis and Sentiment Classification of Extended Reality Product Content,” Klik Kaji. Ilm. Inform. dan Komput., vol. 4, no. 4, pp. 2197–2208, 2024, doi: 10.30865/klik.v4i4.1710.

L. G. R. Putra, Mayadi, and I. N. D. Setiaji, “Klasifikasi Jenis Client Menggunakan Algoritma Decision Tree Cart,” JSI J. Sist. Inf., vol. 14, no. 2, pp. 2842–2855, 2022, doi: 10.30812/jsi.v14i2.18826.

Y. A. Singgalen, “Performance Evaluation of SVM Algorithm in Sentiment Classification : A Visual Journey of Wonderful Indonesia Content,” KLIK Kaji. Ilm. Inform. dan Komput., vol. 4, no. 4, pp. 2078–2087, 2024, doi: 10.30865/klik.v4i4.1709.

Y. A. Singgalen, “Sentiment Classification of Over-Tourism Issues in Responsible Tourism Content using Naïve Bayes Classifier,” J. Comput. Syst. Informatics, vol. 5, no. 2, pp. 275–285, 2024, doi: 10.47065/josyc.v5i2.4904.

Y. A. Singgalen, “Sentiment Classification of Robot Hotel Content using NBC and SVM Algorithm,” J. Comput. Syst. Informatics, vol. 5, no. 2, pp. 442–453, 2024, doi: 10.47065/josyc.v5i2.4924.

Y. A. Singgalen, “Sentiment Classification of Climate Change and Tourism Content Using Support Vector Machine,” J. Comput. Syst. Informatics, vol. 5, no. 2, pp. 357–367, 2024, doi: 10.47065/josyc.v5i2.4908.

Z. Li, R. Li, and G. Jin, “Sentiment analysis of danmaku videos based on naïve bayes and sentiment dictionary,” IEEE Access, vol. 8, pp. 75073–75084, 2020, doi: 10.1109/ACCESS.2020.2986582.

Y. Chen, L. Chen, and Y. Pan, “Social media influencer endorsement: the conditional effects of product attribute description in sponsored influencer videos,” J. Mark. Manag., vol. 00, no. 00, pp. 1–29, 2024, doi: 10.1080/0267257X.2024.2305748.

Z. H. Gong and S. Holiday, “Parasocial Interaction Message Elements and Disclosure Timing in Nano- and Microinfluencers’ Sponsored Content As Alternative Explanations for Follower Count’s Influence on Engagement,” J. Interact. Advert., vol. 23, no. 4, pp. 374–387, 2023, doi: 10.1080/15252019.2023.2236093.

P. Tan-intaraarj, “Exploring influence attempts, wishful identification, parasocial relationships, and behavioral loyalty among Thai game live-streamers and their viewers,” Asian J. Commun., vol. 34, no. 2, pp. 178–194, 2024, doi: 10.1080/01292986.2024.2315580.

H. Jodén and J. Strandell, “Building viewer engagement through interaction rituals on,” Inf. Commun. Soc., vol. 25, no. 13, pp. 1969–1986, 2022, doi: 10.1080/1369118X.2021.1913211.

M. Kim and J. Benenson, “Arts and Culture Nonprofits as Civic Actors : Mapping Audience , Community , and Civic Engagement in Nonprofit Organizations Arts and Culture Nonprofits as Civic Actors : Mapping,” J. Arts Manag. Law, Soc., vol. 53, no. 4, pp. 247–265, 2023, doi: 10.1080/10632921.2023.2240132.

C. Doberstein and C. Doberstein, “How Public Servants Confront Common Dilemmas in Public Engagement : Evidence from a Survey of Canadian Public Officials How Public Servants Confront Common Dilemmas in Public Engagement : Evidence from a Survey of Canadian Public Officials,” Int. J. Public Adm., vol. 47, no. 1, pp. 57–67, 2024, doi: 10.1080/01900692.2022.2085299.

E. McLuskie, “The Public Engagement Industry: Distancing Publics through Managed Engagement and Ideologised Transparency,” Javnost, vol. 30, no. 3, pp. 299–321, 2023, doi: 10.1080/13183222.2023.2201761.

M. Kersting, R. Steier, and G. Venville, “Exploring participant engagement during an astrophysics virtual reality experience at a science festival,” Int. J. Sci. Educ. Part B Commun. Public Engagem., vol. 11, no. 1, pp. 17–34, 2021, doi: 10.1080/21548455.2020.1857458.

M. Kersting, J. Bondell, R. Steier, and M. Myers, “Virtual reality in astronomy education: reflecting on design principles through a dialogue between researchers and practitioners,” Int. J. Sci. Educ. Part B Commun. Public Engagem., pp. 1–20, 2023, doi: 10.1080/21548455.2023.2238871.

D. Amangeldi, A. Usmanova, and P. Shamoi, “Understanding Environmental Posts: Sentiment and Emotion Analysis of Social Media Data,” IEEE Access, vol. 12, no. March, pp. 33504–33523, 2024, doi: 10.1109/ACCESS.2024.3371585.

M. Paoli and B. Pezzotti, “Social critique and viewer’s response in the Italian Gangster film: the case of Bandits in Milan (1968) and Romanzo Criminale (2005),” Stud. Eur. Cine., vol. 17, no. 3, pp. 249–264, 2020, doi: 10.1080/17411548.2020.1798103.

M. Li, M. Cheng, V. Quintal, and I. Cheah, “From live streamer to viewer: exploring travel live streamer persuasive linguistic styles and their impacts on travel intentions,” J. Travel Tour. Mark., vol. 40, no. 8, pp. 764–777, 2023, doi: 10.1080/10548408.2023.2294071.

S. Dickinson and S. Dickinson, “Watching the disaster unfold : geographies of engagement with live-streamed extreme weather with live-streamed extreme weather ABSTRACT,” Environ. Hazards, pp. 1–19, 2024, doi: 10.1080/17477891.2024.2324058.

J. Kwon, H. Lin, L. Deng, T. Dellicompagni, and M. Y. Kang, “Computerized emotional content analysis: empirical findings based on charity social media advertisements,” Int. J. Advert., vol. 41, no. 7, pp. 1314–1337, 2022, doi: 10.1080/02650487.2021.2012070.

W. Megarry and K. Hadick, “Lessons from the Edge: Assessing the impact and efficacy of digital technologies to stress urgency about climate change and cultural heritage globally,” Hist. Environ. Policy Pract., vol. 12, no. 3–4, pp. 336–355, 2021, doi: 10.1080/17567505.2021.1944571.

A. I. Ramaano, “Potential of ecotourism as a mechanism to buoy community livelihoods: the case of Musina Municipality, Limpopo, South Africa,” J. Bus. Socio-economic Dev., vol. 1, no. 1, pp. 47–70, Jan. 2021, doi: 10.1108/jbsed-02-2021-0020.

E. Del Soldato and S. Massari, “Creativity and digital strategies to support food cultural heritage in Mediterranean rural areas,” EuroMed J. Bus., vol. 19, no. 1, pp. 113–137, Jan. 2024, doi: 10.1108/EMJB-05-2023-0152.

M. Das and B. Chatterjee, “Ecotourism a solution or deception for conservation: a case of Bhitarkanika Wildlife Sanctuary, Odisha, India,” J. Hosp. Tour. Insights, vol. 6, no. 3, pp. 1380–1399, Jan. 2023, doi: 10.1108/JHTI-12-2021-0336.

N. Koenig-lewis, A. Palmer, and Y. Asaad, “Linking engagement at cultural festivals to legacy impacts,” J. Sustain. Tour., vol. 29, no. 11–12, pp. 1810–1831, 2021, doi: 10.1080/09669582.2020.1855434.

J. Khan, N. Ahmad, S. Khalid, F. Ali, and Y. Lee, “Sentiment and Context-Aware Hybrid DNN With Attention for Text Sentiment Classification,” IEEE Access, vol. 11, no. February, pp. 28162–28179, 2023, doi: 10.1109/ACCESS.2023.3259107.

F. Yin, Y. Wang, J. Liu, and L. Lin, “The Construction of Sentiment Lexicon Based on Context-Dependent Part-of-Speech Chunks for Semantic Disambiguation,” IEEE Access, vol. 8, pp. 63359–63367, 2020, doi: 10.1109/ACCESS.2020.2984284.

B. M. A. Tahayna, R. K. Ayyasamy, and R. Akbar, “Automatic Sentiment Annotation of Idiomatic Expressions for Sentiment Analysis Task,” IEEE Access, vol. 10, no. October, pp. 122234–122242, 2022, doi: 10.1109/ACCESS.2022.3222233.

L. A. Siminoff, K. Chansiri, G. Alolod, and H. M. Gardiner, “Culturally Tailored and Community-Based Social Media Intervention to Promote Organ Donation Awareness among Asian Americans: ‘Heart of Gold,’” J. Health Commun., vol. 27, no. 7, pp. 450–459, 2022, doi: 10.1080/10810730.2022.2119445.

D. Xi, J. Zhou, W. Xu, and L. Tang, “Discrete Emotion Synchronicity and Video Engagement on Social Media: A Moment-to-Moment Analysis,” Int. J. Electron. Commer., vol. 28, no. 1, pp. 108–144, 2024, doi: 10.1080/10864415.2023.2295072.

K. Kim, H. S. Kim, M. Y. Chung, and Y. Kim, “Do viewers really talk about ads during commercial breaks? Findings from a South Korean social TV platform,” Asian J. Commun., vol. 31, no. 4, pp. 299–317, 2021, doi: 10.1080/01292986.2021.1945118.

K. Farhat, W. Aslam, and S. S. M. Mokhtar, “Beyond Social Media Engagement: Holistic Digital Engagement and a Social Identity Perspective,” J. Internet Commer., vol. 20, no. 3, pp. 319–354, 2021, doi: 10.1080/15332861.2021.1905474.

N. Zhao, H. Gao, X. Wen, and H. Li, “Combination of convolutional neural network and gated recurrent unit for aspect-based sentiment analysis,” IEEE Access, vol. 9, pp. 15561–15569, 2021, doi: 10.1109/ACCESS.2021.3052937.

K. R. Mabokela, T. Celik, and M. Raborife, “Multilingual Sentiment Analysis for Under-Resourced Languages: A Systematic Review of the Landscape,” IEEE Access, vol. 11, no. February, pp. 15996–16020, 2023, doi: 10.1109/ACCESS.2022.3224136.

T. Hu, B. She, L. Duan, H. Yue, and J. Clunis, “A systematic spatial and temporal sentiment analysis on geo-tweets,” IEEE Access, vol. 8, pp. 8658–8667, 2020, doi: 10.1109/ACCESS.2019.2961100.

T. Lin and I. Joe, “An Adaptive Masked Attention Mechanism to Act on the Local Text in a Global Context for Aspect-Based Sentiment Analysis,” IEEE Access, vol. 11, no. May, pp. 43055–43066, 2023, doi: 10.1109/ACCESS.2023.3270927.

H. Liu, X. Chen, and X. Liu, “A Study of the Application of Weight Distributing Method Combining Sentiment Dictionary and TF-IDF for Text Sentiment Analysis,” IEEE Access, vol. 10, pp. 32280–32289, 2022, doi: 10.1109/ACCESS.2022.3160172.

K. A. Stofer, D. Hanson, and K. Hecht, “Scientists need professional development to practice meaningful public engagement,” J. Responsible Innov., vol. 10, no. 1, 2023, doi: 10.1080/23299460.2022.2127672.

N. AbiGhannam and A. Dudo, “Examining the perceived value of a prestigious science engagement award: views of applicants, finalists, and awardees,” Int. J. Sci. Educ. Part B Commun. Public Engagem., vol. 11, no. 3, pp. 259–272, 2021, doi: 10.1080/21548455.2021.1969605.

L. Lin, S. Li, X. Huang, and F. Chen, “Longitudinal changes of student engagement in social annotation,” Distance Educ., vol. 45, no. 1, pp. 103–121, 2024, doi: 10.1080/01587919.2024.2303488.

Bila bermanfaat silahkan share artikel ini

Berikan Komentar Anda terhadap artikel Implementation of SVM, k-NN, and DT for Toxicity and Sentiment Classification of AWA Vlog Content in Wasur National Park


  • There are currently no refbacks.


Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.

STMIK Budi Darma
Secretariat: Sisingamangaraja No. 338 Telp 061-7875998

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.