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あ ぁ か が さ ざ た だ な は ば ぱ ま や ゃ ら わ ゎ ん い ぃ き ぎ し じ ち ぢ に ひ び ぴ み り う ぅ く ぐ す ず つ づ っ ぬ ふ ぶ ぷ む ゆ ゅ る え ぇ け げ せ ぜ て で ね へ べ ぺ め れ お ぉ こ ご そ ぞ と ど の ほ ぼ ぽ も よ ょ ろ を
ア ァ カ サ ザ タ ダ ナ ハ バ パ マ ヤ ャ ラ ワ ヮ ン イ ィ キ ギ シ ジ チ ヂ ニ ヒ ビ ピ ミ リ ウ ゥ ク グ ス ズ ツ ヅ ッ ヌ フ ブ プ ム ユ ュ ル エ ェ ケ ゲ セ ゼ テ デ ヘ ベ ペ メ レ オ ォ コ ゴ ソ ゾ ト ド ノ ホ ボ ポ モ ヨ ョ ロ ヲ ―

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예시)
  • 中文 을 입력하시려면 zhongwen을 입력하시고 space를누르시면됩니다.
  • 北京 을 입력하시려면 beijing을 입력하시고 space를 누르시면 됩니다.
ㅥ ㅦ ㅧ ㅨ ㅩ ㅪ ㅫ ㅬ ㅭ ㅮ ㅯ ㅰ ㅱ ㅲ ㅳ ㅴ ㅵ ㅶ ㅷ ㅸ ㅹ ㅺ ㅻ ㅼ ㅽ ㅾ ㅿ ㆀ ㆁ ㆂ ㆃ ㆄ ㆅ ㆆ ㆇ ㆈ ㆉ ㆊ ㆋ ㆌ ㆍ ㆎ
Α Β Γ Δ Ε Ζ Η Θ Ι Κ Λ Μ Ν Ξ Ο Π Ρ Σ Τ Υ Φ Χ Ψ Ω α β γ δ ε ζ η θ ι κ λ μ ν ξ ο π ρ σ τ υ φ χ ψ ω
á à Á À é è É È ç Ç ê
Ä Ö Ü ä ö ü ß
ְ ֳ ֲ ֱ ָ ַ ֵ ֶ ִ ֹ ּ ֻ ׂ ׁ ּ פ ם ן ו ט א ר ק ף ך ל ח י ע כ ג ד ש ץ ת צ מ נ ה ב
‘ ’ “ ” 〔 〕 〈 〉 「 」 『 』 【 】 ＂ （ ） ［ ］ ｛ ｝
± × ÷ ≠ ≤ ≥ ∞ ∴ ♂ ♀ ∠ ⊥ ⌒ ∂ ∇ ≡ ≒ ≪ ≫ √ ∽ ∝ ∵ ∫ ∬ ∈ ∋ ⊆ ⊇ ⊂ ⊃ ∪ ∩ ∧ ∨ ￢ ⇒ ⇔ ∀ ∃ ∮ ∑ ∏ ＋ － ＜ ＝ ＞
、 。 · ‥ … ¨ 〃 ― ∥ ＼ ∼ ´ ～ ˇ ˘ ˝ ˚ ˙ ¸ ˛ ¡ ¿ ː ！ ＇ ， ． ／ ： ； ？ ＾ ＿ ｀ ｜
½ ⅓ ⅔ ¼ ¾ ⅛ ⅜ ⅝ ⅞ ¹ ² ³ ⁴ ⁿ ₁ ₂ ₃ ₄
Æ Ð Ħ IJ Ł Ø Œ Þ Ŧ Ŋ æ đ ð ħ ı ij ĸ ŀ ł ø œ ß þ ŧ ŋ ʼn
А Б В Г Д Е Ё Ж З И Й К Л М Н О П Р С Т У Ф Х Ц Ч Ш Щ Ъ Ы Ь Э Ю Я а б в г д е ё ж з и й к л м н о п р с т у ф х ц ч ш щ ъ ы ь э ю я
′ ″ ℃ Å ￠ ￡ ￥ ¤ ℉ ‰ ＄ ％ Ｆ ￦ ㎕ ㎖ ㎗ ℓ ㎘ ㏄ ㎣ ㎤ ㎥ ㎦ ㎙ ㎚ ㎛ ㎜ ㎝ ㎞ ㎟ ㎠ ㎡ ㎢ ㏊ ㎍ ㎎ ㎏ ㏏ ㎈ ㎉ ㏈ ㎧ ㎨ ㎰ ㎱ ㎲ ㎳ ㎴ ㎵ ㎶ ㎷ ㎸ ㎹ ㎀ ㎁ ㎂ ㎃ ㎄ ㎺ ㎻ ㎽ ㎾ ㎿ ㎐ ㎑ ㎒ ㎓ ㎔ Ω ㏀ ㏁ ㎊ ㎋ ㎌ ㏖ ㏅ ㎭ ㎮ ㎯ ㏛ ㎩ ㎪ ㎫ ㎬ ㏝ ㏐ ㏓ ㏃ ㏉ ㏜ ㏆
§ ※ ☆ ★ ○ ● ◎ ◇ ◆ □ ■ △ ▽ → ← ↑ ↓ ↔ 〓 ◁ ◀ ▷ ▶ ♤ ♠ ♡ ♥ ♧ ♣ ⊙ ◈ ▣ ◐ ◑ ▒ ▤ ▥ ▨ ▧ ▦ ▩ ♨ ☏ ☎ ☜ ☞ † ‡ ↕ ↗ ↙ ↖ ↘ ♭ ♩ ♪ ♬ ㉿ ㈜ № ㏇ ™ ㏂ ㏘ ℡ ＃ ＆ ＊ ＠ ª º
ⅰ ⅱ ⅲ ⅳ ⅴ ⅵ ⅶ ⅷ ⅸ ⅹ Ⅰ Ⅱ Ⅲ Ⅳ Ⅴ Ⅵ Ⅶ Ⅷ Ⅸ Ⅹ
ا ب ت ث ج ح خ د ذ ر ز س ش ص ض ط ظ ع غ ف ق ک ل م ن ه و ی
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      악성 댓글 기반 이슈 분류를 위한 토픽 클러스터링 연구 = A Study on Topic Clustering for Issue Classification Based on Malicious Comments

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      https://www.riss.kr/link?id=A110113443

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      다국어 초록 (Multilingual Abstract) kakao i 다국어 번역

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      Purpose This study aims to analyze online malicious comments not as simple emotional expressions but as issue-based discourse structures, quantitatively identifying the formation and diffusion patterns of social conflicts.


      Design/Methodology/Approach A total of 59,654 comments from the KBS News YouTube channel were collected between May and September 2025. A dictionary of 113 malicious keywords was constructed, and ten major topics were derived using Sentence-BERT–based BERTopic modeling. The core keywords of each topic were visualized through co-occurrence network (SNA) analysis, and weekly weight variations were examined using a heatmap-based time series analysis.


      Findings “Political conflict and power criticism” and “media distrust” emerged as the dominant issues, while keywords such as rebellion, impeachment, fake news, and fraud functioned as central hubs in the network. Particularly during the third week of June and the second week of September, an issue-reactive pattern appeared, indicating that malicious comments serve as a structural medium for the spread of public opinion online.
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      Purpose This study aims to analyze online malicious comments not as simple emotional expressions but as issue-based discourse structures, quantitatively identifying the formation and diffusion patterns of social conflicts. Design/Methodology/Approac...

      Purpose This study aims to analyze online malicious comments not as simple emotional expressions but as issue-based discourse structures, quantitatively identifying the formation and diffusion patterns of social conflicts.


      Design/Methodology/Approach A total of 59,654 comments from the KBS News YouTube channel were collected between May and September 2025. A dictionary of 113 malicious keywords was constructed, and ten major topics were derived using Sentence-BERT–based BERTopic modeling. The core keywords of each topic were visualized through co-occurrence network (SNA) analysis, and weekly weight variations were examined using a heatmap-based time series analysis.


      Findings “Political conflict and power criticism” and “media distrust” emerged as the dominant issues, while keywords such as rebellion, impeachment, fake news, and fraud functioned as central hubs in the network. Particularly during the third week of June and the second week of September, an issue-reactive pattern appeared, indicating that malicious comments serve as a structural medium for the spread of public opinion online.

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      다국어 초록 (Multilingual Abstract) kakao i 다국어 번역

      영어
      한국어
      Purpose This study aims to analyze online malicious comments not as simple emotional expressions but as issue-based discourse structures, quantitatively identifying the formation and diffusion patterns of social conflicts.




      Design/Methodology/Approach A total of 59,654 comments from the KBS News YouTube channel were collected between May and September 2025. A dictionary of 113 malicious keywords was constructed, and ten major topics were derived using Sentence-BERT–based BERTopic modeling. The core keywords of each topic were visualized through co-occurrence network (SNA) analysis, and weekly weight variations were examined using a heatmap-based time series analysis.




      Findings “Political conflict and power criticism” and “media distrust” emerged as the dominant issues, while keywords such as rebellion, impeachment, fake news, and fraud functioned as central hubs in the network. Particularly during the third week of June and the second week of September, an issue-reactive pattern appeared, indicating that malicious comments serve as a structural medium for the spread of public opinion online.
      번역하기

      Purpose This study aims to analyze online malicious comments not as simple emotional expressions but as issue-based discourse structures, quantitatively identifying the formation and diffusion patterns of social conflicts. Design/Methodology/Appro...

      Purpose This study aims to analyze online malicious comments not as simple emotional expressions but as issue-based discourse structures, quantitatively identifying the formation and diffusion patterns of social conflicts.




      Design/Methodology/Approach A total of 59,654 comments from the KBS News YouTube channel were collected between May and September 2025. A dictionary of 113 malicious keywords was constructed, and ten major topics were derived using Sentence-BERT–based BERTopic modeling. The core keywords of each topic were visualized through co-occurrence network (SNA) analysis, and weekly weight variations were examined using a heatmap-based time series analysis.




      Findings “Political conflict and power criticism” and “media distrust” emerged as the dominant issues, while keywords such as rebellion, impeachment, fake news, and fraud functioned as central hubs in the network. Particularly during the third week of June and the second week of September, an issue-reactive pattern appeared, indicating that malicious comments serve as a structural medium for the spread of public opinion online.

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