References
- Korean Internet & Security Agency, "Internet Use Survey Summary Report," Korean Internet & Security Agency (KISA), 2014.
- Comments, [Internet]. Available: https://ko.wikipedia.org/wiki/.
- E. J. No, "The Constitutional Study on Internet Comments," a master's thesis SungKyunKwan University, Aug. 2014.
- Prosecution service, Internet malicious comments illegal act processing method implementation press release, Apr. 2015.
- S. S. Kang, "A Normalization Method of Distorted Korean SMS Sentences for Spam Message Filtering," Korea Information Processing Society, vol. 3, no. 7, pp.271-276, Jul. 2014.
- K. S. Shim and J. H. Yang, "High Speed Korean Morphological Analysis based on Adjacency Condition Check," Korean Institute of Information Scientists and Engineers, vol. 31, no. 1, pp.89-99, Jan. 2004.
- J. S. Song and S. W. Lee, "Automatic Construction of Positive/Negative Feature-Predicate Dictionary for Polarity Classification of Product Reviews," Korean Institute of Information Scientists and Engineers, vol. 38, no. 3, pp.157-168, Mar. 2011.
- S. W. Kim and N. K. Kim, "A Study on the Effect of Using Sentiment Lexicon in Opinion Classification," Korea Intelligent Information System Society, vol. 20, no. 1, pp.133-148, Mar. 2014.
- E. J. You, Y. S. Kim, N. K. Kim and S, Y. Jung, "Predicting the Direction of the Stock Index by Using a Domain-Specific Sentiment Dictionary," Korea Intelligent Information System Society, vol. 19, no. 1, pp.95-110, Mar. 2013. https://doi.org/10.13088/jiis.2013.19.1.095
- Corinna Cortes and Vladimir Vapnik, "Support vector networks," Machine Learning 20, pp.273-297, 1995.
- M. S. Kim and S. S. Kang, "A Design and Implementation of Malicious Web Log Identification System by Using SVM," 18st Annual Conference on Human and Language Technology, pp.285-289, Oct. 2006.
- M. Y. Bae and J. W. Cha, "Comments Classification System using Topic Signature," Korean Institute of Information Scientists and Engineers, vol. 35, no. 12, pp.774-779, Dec. 2008.
- H. J. Kim, Y. M. Yoon and B. M. Lee, "Prediction System for Abusive Postings using Enhanced FFP," Journal of Korean Institute of Information Technology, vol. 9, no. 1. pp.207-216, Jan. 2011.
- the fancake, [Internet]. Available: https://thefancake.co.kr/
- K. H. Joe, "A Study Text Typological of Internet Comments," The Textlinguistic Society of Korea, vol. 23, pp.203-230, Nov. 2007.
- S. S. Kang and K. B. Hwang, "A Language Independent n-gram Model for Word Segmentation," Advances in Artificial Intelligence 2006, vol. 4303, pp.557-565, Dec. 2006.
Cited by
- SVM과 협업적 필터링 기법을 이용한 소비자 맞춤형 시장 분석 기법 설계 vol.9, pp.6, 2016, https://doi.org/10.17661/jkiiect.2016.9.6.609
- 부분방전 패턴인식을 위해 EMC센서를 이용한 최적화된 RBFNNs 분류기 설계 vol.66, pp.9, 2016, https://doi.org/10.5370/kiee.2017.66.9.1392
- 소셜 미디어 텍스트를 이용한 장소 선호도 분석 기법 vol.25, pp.4, 2016, https://doi.org/10.7319/kogsis.2017.25.4.055
- A Comparison Study on Performance of Malicious Comment Classification Models Applied with Artificial Neural Network vol.20, pp.7, 2019, https://doi.org/10.9728/dcs.2019.20.7.1429
- Analyzing Dissatisfaction Factors of Weather Service Users Using Twitter and News Headlines vol.15, pp.4, 2016, https://doi.org/10.5392/ijoc.2019.15.4.065
- 하이웨이 네트워크 기반 CNN 모델링 및 사전 외 어휘 처리 기술을 활용한 악성 댓글 분류 연구 vol.29, pp.3, 2016, https://doi.org/10.5859/kais.2020.29.3.103
- 딥러닝 기술을 활용한 차별 및 혐오 표현 탐지 : 어텐션 기반 다중 채널 CNN 모델링 vol.24, pp.12, 2016, https://doi.org/10.6109/jkiice.2020.24.12.1595