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๊ฒ€์ฆ๋œ ํŒŒํŠธ๋„ˆ ์ œํœด์‚ฌ ์ž๋ฃŒ

Classification of Emotional Vocabulary Based on Emoticon for Mobile SNS(Social Network Service) Messenger

8 ํŽ˜์ด์งฟ’
์–ด๋„๋น„ PDF
์ตœ์ดˆ๋“ฑ๋ก์ผ 2023.04.05 ์ตœ์ข…์ ฟ’์ž‘์ผ 2018.03
8P ๋ฏธ๋้ฉ๋ณด๊ธฐ
Classification of Emotional Vocabulary Based on Emoticon for Mobile SNS(Social Network Service) Messenger
  • * ๋ณธ ๋ฌธ์„œ๋Š” ๋ฐฐํฌ์šฉ์œผ๋กœ ๋ณต์‚ฌ ๋ฐ ํŽธ์ง‘์ด ๋ถˆ๊ฐ€ํ•ฉ๋‹ˆ๋‹ค.

    ๋ฏธ๋้ฉ๋ณด๊ธฐ

    ์„œ์่ง์ •๋ต–

    ยท ๋ฐœํ–‰๊ธฐ๊ด€ : ํ•œ๊ตญ์ปดํ“จํ„ฐ๊ฒŒ์ž„ํ•™ํšŒ
    ยท ์ˆ˜๋ก์ง€ ์ •๋ณด : ํ•œ๊ตญ์ปดํ“จํ„ฐ๊ฒŒ์ž„ํ•™ํšŒ ๋…ผ๋ๅฉ์ง€ / 31๊ถŒ / 1ํ˜ธ
    ยท ์ €์ž๋ช… : Eun Ah Lee, Yoon Ah Lim, Jieun Kwon

    ๋ชฉ์ฐจ

    ABSTRACT
    1. Introduction
    1.1 Research Background and Purpose
    1.2 Research methods and scope
    2. Mobile SNS messenger communication
    2.1 Mobile SNS messenger-basedcommunication
    2.2 Emoticon and emotional vocabulary foremotional communication
    3. Mobile SNS Messenger Emoticonbased emotional vocabularyextraction and classification
    3.1 Experiment range and process
    3.2 Emotional vocabulary collection andappropriate vocabulary extraction
    3.2.1 Emotional vocabulary collection
    3.2.2 Fit vocabulary extraction
    3.3 Emotional vocabulary classification andmodel
    4. Conclusion
    Acknowledgement
    Referenece

    ์ดˆ๋ก

    ์ตœ๊ทผ ์ฆ๊ฐ€๋˜๊ณ  ์žˆ๋Š” ๋ชจ๋ฐ”์ผ SNS(Social Network Service)๋ฅผ ํ†ตํ•œ ๋งค๊ฐœ(Mediated) ์ปค๋ฎค๋‹ˆ์ผ€์ด์…˜์—์„œ ์ž์‹ ์˜ ๊ฐ์„ฑ์„ ํ‘œํ˜„ ๊ฐ€๋Šฅํ•œ ์ด๋ชจํ‹ฐ์ฝ˜์„ ํ™œ์šฉํ•˜์—ฌ ๋Œ€ํ™”ํ•˜๋Š” ๊ฐ์„ฑ ์ปค๋ฎค๋‹ˆ์ผ€์ด์…˜์ด ๋ฐœ๋‹ฌํ•˜๊ณ  ์žˆ๋‹ค. ์ด๋ชจํ‹ฐ์ฝ˜ ๊ฐœ๋ฐœ์ด ์ฆ๊ฐ€ ํ•˜๊ณ  ์‚ฌ์šฉ์ด ๋Œ€์ค‘ํ™”๊ฐ€ ๋จ์— ๋”ฐ๋ผ, ์‚ฌ์šฉ์ž๊ฐ€ ์›ํ•˜๋Š” ๊ฐ์„ฑ ํ‘œํ˜„์ด๋‚˜ ์˜๋ฏธ๋ฅผ ์ƒ์ง•ํ•˜๋Š” ์•„์ดํ…œ์— ๋Œ€ํ•œ ์š”๊ตฌ๊ฐ€ ํ™•๋Œ€ ๋˜๊ณ  ์žˆ๋‹ค. ๋˜ํ•œ, ๋™์ผํ•œ ์ด๋ชจํ‹ฐ์ฝ˜์ด๋ผ๋„ ์‚ฌ์šฉ์ž์— ๋”ฐ๋ผ ๋‹ค๋ฅด๊ฒŒ ํ•ด์„ํ•  ์ˆ˜ ์žˆ์œผ๋ฉฐ, ๋””์ž์ด๋„ˆ์˜ ์˜๋„ํ•œ ๊ฐ์„ฑ ํ‘œํ˜„์— ๋Œ€ํ•ด ์‚ฌ์šฉ์ž์˜ ์˜๋ฏธ ํ•ด์„์ด ์ƒ์ดํ•  ์ˆ˜ ์žˆ๋‹ค. ๋”ฐ๋ผ์„œ ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ๋ชจ๋ฐ”์ผ SNS ๋ฉ”์‹ ์ €์—์„œ ์ด๋ชจํ‹ฐ์ฝ˜์„ ์ด์šฉํ•œ ์ปค๋ฎค๋‹ˆ์ผ€์ด์…˜์„ ์œ„ํ•ด ์‚ฌ์šฉ๋˜๋Š” ๊ฐ์„ฑ ์–ดํœ˜๋ฅผ ์—ฐ๊ตฌํ•˜๊ณ  ๋ถ„๋ฅ˜ํ•˜์—ฌ ๊ฐ์„ฑ ์ปค๋ฎค๋‹ˆ์ผ€์ด์…˜๊ณผ ๊ด€๋ จ๋œ ์ด๋ชจํ‹ฐ์ฝ˜ ๊ฐœ๋ฐœ์˜ ์ดˆ์„์„ ๋งˆ๋ จํ•˜๊ณ ์ž ํ•œ๋‹ค. ์ฆ‰, ์‚ฌ์šฉ์ž ๊ด€์ ์—์„œ ์ด๋ชจํ‹ฐ์ฝ˜์— ๊ธฐ๋ฐ˜ํ•˜์—ฌ ํ‘œํ˜„ํ•˜๊ณ ์ž ํ•˜๋Š” ๊ฐ์„ฑ ์–ดํœ˜์— ๋Œ€ํ•œ ๋ถ„๋ฅ˜์™ฟ’ ๋ชจ๋ธ์„ ์ œ์•ˆํ•œ๋‹ค. ๋ณธ ์—ฐ๊ตฌ๋ฅผ ์œ„ํ•ด ์ฒซ์งธ, ๋ฌธํ—Œ์กฐ์‚ฌ๋ฅผ ๊ธฐ๋ฐ˜์œผ๋กœ ๊ฐ์„ฑ ํ˜•์šฉ์‚ฌ๋ฅผ ์ˆ˜์ง‘ํ•˜๊ณ  ์„ค๋ฌธ, ํ†ต๊ณ„ ๋ถ„์„ ๋ฐ FGI (Focus Group Interview)๋ฅผ ํ†ตํ•ด 1์ฐจ ๊ฐ์„ฑ ์–ดํœ˜๋ฅผ ์ถ”์ถœํ•œ๋‹ค. ๋‘˜์งธ, 2์ฐจ ์„ค๋ฌธ์กฐ์‚ฌ ๋ฐ ํ†ต๊ณ„๋ถ„์„์„ ํ†ตํ•ด ์ตœ์ข… ์ ํ•ฉ ์–ดํœ˜๋ฅผ ์ถ”์ถœํ•œ๋‹ค. ์…‹์งธ, ์ตœ์ข… ์ถ”์ถœ๋œ ์–ดํœ˜๋ฅผ ๋ฐ”ํƒ•์œผ๋กœ ๋‹ค์ฐจ์›์ฒ™๋„ ๋ถ„์„์„ ์‹คํ–‰ํ•˜์—ฌ ์–ดํœ˜ ๋ชจ๋ธ์„ ๋„์ถœํ•˜๊ณ  ๊ฐ์„ฑ ์–ดํœ˜๋ฅผ ๋ถ„๋ฅ˜ํ•œ๋‹ค. ๊ทธ ๊ฒฐ๊ณผ โ€˜๋ฏธ์•ˆํ•˜๋‹คโ€™, โ€˜๋ฐ”์˜๋‹คโ€™, โ€˜๋ฐฐ๊ณ ํ”„๋‹คโ€™, โ€˜์–ด๋ ต๋‹คโ€™, โ€˜์Šฌํ”„๋‹คโ€™, โ€˜๋‚ ์”จ๊ฐ€ ์ถฅ๊ฑฐ๋‚˜ ๋ฅ๋‹คโ€™, โ€˜์ง€ ๋ฃจํ•˜๋‹คโ€™, โ€˜๋ถ€๋„๋Ÿฝ๋‹คโ€™, โ€˜๊ถ๊ธˆํ•˜๋‹คโ€™, โ€˜๋งŒ์กฑํ•˜๋‹คโ€™, โ€˜์ข‹๋‹คโ€™, โ€˜์•„๋ฆ„๋‹ต๋‹คโ€™, โ€˜ํŽธ์•ˆํ•˜๋‹คโ€™ ์˜ 13๊ฐœ ์–ดํœ˜๋กœ ๋ถ„๋ฅ˜๋˜์—ˆ๋‹ค.

    ์˜์–ด์ดˆ๋ก

    Recently, emotional communication has been developed by emoticons that express user emotion in mediated communication through mobile Social Network Service(SNS). As the development of emoticons increases and the usage becomes more popular, there is a growing demand for items that express the emotional expression and desired meaning by the user. And also mis-communication can occur through different interpretation amongst users. Additionally, the meaning interpreted by the users may be different from the designersโ€™ intended emotional expressions. In this study, we propose a model by classifying emotional vocabularies. First, we collected emotional adjectives and extracted the first set of vocabularies with questionnaires, statistical analysis and FGI (Focus Group Interview). Second, we extracted the final set of proper vocabulary from the first set of vocabularies with a second set of questionnaires and statistical analysis. Third, with the final set of vocabularies an emotional vocabulary model was built based on the multidimensional scale analysis. As a result, the model was classified into 13 categories, which are as follows: sorry, busy, hungry, difficult, sad, the weather is cold or hot, boring, ashamed, curious, satisfy, good, beautiful, and comfortable.

    ์ฐธ๊ณ ์ž๋ฃŒ

    ยท ์—†์Œ
  • ์ž๋ฃŒํ›„๊ธฐ

    Ai ๋ฆฌ๋ทฐ
    ์งฟ’์‹ํŒ๋งค์ž๊ฐ€ ์ œ๊ณตํ•˜๋Š” ์ž๋ฃŒ๋Š” ์งˆ์ด ๋งค์šฐ ๋†’๊ณ , ์ฃผ์ œ์— ๋Œ€ํ•œ ๊นŠ์ด ์žˆ๋Š” ๋ถ„์„์ด ์ธ์ƒ์ ์ž…๋‹ˆ๋‹ค. ์ดํ•ดํ•˜๊ธฐ ์‰ฌ์šด ์„ค๋ช…๊ณผ ๋‹ค์–‘ํ•œ ์˜ˆ์‹œ ๋•๋ถ„์— ํ™œ์šฉํ•˜๊ธฐ ํŽธํ–ˆ์Šต๋‹ˆ๋‹ค. ์ •๋ง ๊ฐ์‚ฌ๋“œ๋ฆฝ๋‹ˆ๋‹ค!
    • ์ž์ฃผ๋ฌป๋Š”์งˆ๋ๅฉ์˜ ๋‹ต๋ณ€์„ ํ™•์ธํ•ด ์ฃผ์„ธ์š”

      ํ•ดํ”ผ์บ ํผ์Šค FAQ ๋”๋ต–๊ธฐ

      ๊ผญ ์•Œ์•„์ฃผ์„ธ์š”

      • ๋ณธ ํ•™์ˆ ๋…ผ๋ๅฉ์€ (์ฃผ)์ฝ”๋้ฉ์•„์Šค์นผ๋ผ์™ฟ’ ๊ฐ ํ•™ํšŒ๊ฐ„์— ์ €์ž‘๊ถŒ๊ณ„์•ฝ์ด ์ฒด๊ฒฐ๋œ ๊ฒƒ์œผ๋กœ AgentSoft๊ฐ€ ์ œ๊ณต ํ•˜๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค.
        ๋ณธ ์ €์ž‘๋ฌผ์„ ๋ถˆ๋ฒ•์ ์œผ๋กœ ์ด์šฉ์‹œ๋Š” ๋ฒ•์ ์ธ ์ œ์žฌ๊ฐ€ ๊ฐ€ํ•ด์งˆ ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค.
      • ํ•ดํ”ผ์บ ํผ์Šค๋Š” ๊ตฌ๋งค์ž์™ฟ’ ํŒ๋งค์ž ๋ชจ๋‘๊ฐ€ ๋งŒ์กฑํ•˜๋Š” ์„œ๋น„์Šค๊ฐ€ ๋˜๋„๋ก ๋…ธ๋ ฅํ•˜๊ณ  ์žˆ์œผ๋ฉฐ, ์•„๋ž˜์˜ 4๊ฐ€์ง€ ์ž๋ฃŒํ™˜๋ถˆ ์กฐ๊ฑด์„ ๊ผญ ํ™•์ธํ•ด์ฃผ์‹œ๊ธฐ ๋ฐ”๋ž๋‹ˆ๋‹ค.
        ํŒŒ์ผ์˜ค๋ฅ˜ ์ค‘๋ณต์ž๋ฃŒ ์ €์ž‘๊ถŒ ์—†์Œ ์„ค๋ช…๊ณผ ์‹ค์ œ ๋‚ด์šฉ ๋ถˆ์ผ์น˜
        ํŒŒ์ผ์˜ ๋‹ค์šด๋กœ๋“œ๊ฐ€ ์ œ๋Œ€๋กœ ๋˜์ง€ ์•Š๊ฑฐ๋‚˜ ํŒŒ์ผํ˜•์‹์— ๋งž๋Š” ํ”„๋กœ๊ทธ๋žจ์œผ๋กœ ์ •์ƒ ์ž‘๋™ํ•˜์ง€ ์•Š๋Š” ๊ฒฝ์šฐ ๋‹ค๋ฅธ ์ž๋ฃŒ์™ฟ’ 70% ์ด์ƒ ๋‚ด์šฉ์ด ์ผ์น˜ํ•˜๋Š” ๊ฒฝ์šฐ (์ค‘๋ณต์ž„์„ ํ™•์ธํ•  ์ˆ˜ ์žˆ๋Š” ๊ทผ๊ฑฐ ํ•„์š”ํ•จ) ์ธํ„ฐ๋„ท์˜ ๋‹ค๋ฅธ ์‚ฌ์ดํŠธ, ์—ฐ๊ตฌ๊ธฐ๊ด€, ํ•™๊ป“, ์„œ์  ๋“ฑ์˜ ์ž๋ฃŒ๋ฅผ ๋„์šฉํ•œ ๊ฒฝ์šฐ ์ž๋ฃŒ์˜ ์„ค๋ช…๊ณผ ์‹ค์ œ ์ž๋ฃŒ์˜ ๋‚ด์šฉ์ด ์ผ์น˜ํ•˜์ง€ ์•Š๋Š” ๊ฒฝ์šฐ

    โ€œํ•œ๊ตญ์ปดํ“จํ„ฐ๊ฒŒ์ž„ํ•™ํšŒ ๋…ผ๋ๅฉ์ง€โ€์˜ ๋‹ค๋ฅธ ๋…ผ๋ๅฉ๋„ ํ™•์ธํ•ด ๋ณด์„ธ์š”!

    ์ฐพ์œผ์‹œ๋˜ ์ž๋ฃŒ๊ฐ€ ์•„๋‹Œ๊ฐ€์š”?

    ์ง€๊ธˆ ๋ณด๋Š” ์ž๋ฃŒ์™ฟ’ ์—ฐ๊ด€๋˜์–ด ์žˆ์–ด์š”!
    ์™ผ์ชฝ ํ™”์‚ดํ‘œ
    ์˜ค๋ฅธ์ชฝ ํ™”์‚ดํ‘œ
    ๋ฌธ์„œ ์ดˆ์•ˆ์„ ์ƒ์„ฑํ•ด์ฃผ๋Š” EasyAI
    ์•ˆ๋…•ํ•˜์„ธ์š”. ํ•ดํ”ผ์บ ํผ์Šค์˜ ๋ฐฉ๋Œ€ํ•œ ์ž๋ฃŒ ์ค‘์—์„œ ์„ ๋ณ„ํ•˜์—ฌ ๋‹น์‹ ๋งŒ์˜ ์ดˆ์•ˆ์„ ๋งŒ๋“ค์–ด์ฃผ๋Š” EasyAI ์ž…๋‹ˆ๋‹ค.
    ์ €๋Š” ์•„๋ž˜์™ฟ’ ๊ฐ™์ด ์ž‘์—…์„ ๋„์™ฟ’๋“œ๋ฆฝ๋‹ˆ๋‹ค.
    - ์ฃผ์ œ๋งŒ ์ž…๋ ฅํ•˜๋ฉด ๋ชฉ์ฐจ๋ถ€ํ„ฐ ๋ณธ๋ฌธ๋‚ด์šฉ๊นŒ์ง€ ์ž๋™ ์ƒ์„ฑํ•ด ๋“œ๋ฆฝ๋‹ˆ๋‹ค.
    - ์žฅ๋ฌธ์˜ ์ฝ˜ํ…์ธ ๋ฅผ ์‰ฝ๊ณ  ๋น ๋ฅด๊ฒŒ ์ž‘์„ฑํ•ด ๋“œ๋ฆฝ๋‹ˆ๋‹ค.
    - ์Šคํ† ์–ด์—์„œ ๋ฌด๋ฃŒ ์บ์‹œ๋ฅผ ๊ณ„์ •๋ณ„๋กœ 1ํšŒ ๋ฐœ๊ธ‰ ๋ฐ›์„ ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค. ์ง€๊ธˆ ๋ฐ”๋กœ ์ฒดํ—˜ํ•ด ๋ณด์„ธ์š”!
    ์ด๋Ÿฐ ์ฃผ์ œ๋“ค์„ ์ž…๋ ฅํ•ด ๋ณด์„ธ์š”.
    - ์œ ์•„์—๊ฒŒ ์ ํ•ฉํ•œ ๋ฌธํ•™์ž‘ํ’ˆ์˜ ๊ธฐ์ค€๊ณผ ํŠน์„ฑ
    - ํ•œ๊ตญ์ธ์˜ ๊ฐ€์น˜๊ด€ ์ค‘์—์„œ ์ •์‹ ์  ๊ฐ€์น˜๊ด€์„ ์ด๋ฃจ๋Š” ๊ฒƒ๋“ค์„ ๋ฌธํ™”์  ๋ฌธ๋ฒ•์œผ๋กœ ์ •๋ฆฌํ•˜๊ณ , ํ˜„๋Œ€ํ•œ๊ตญ์‚ฌํšŒ์—์„œ ์ผ์–ด๋‚˜๋Š” ์‚ฌ๊ฑด๊ณผ ์‚ฌ๊ณ ๋ฅผ ๋น„๊ตํ•˜์—ฌ ์ž์‹ ์˜ ์˜๊ฒฌ์œผ๋กœ ๊ธฐ์ˆ ํ•˜์„ธ์š”
    - ์ž‘๋ณ„์ธ์‚ฌ ๋…ํ›„๊ฐ
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    ์ฑ—๋ด‡์œผ๋กœ ๊ฐ„ํŽธํ•˜๊ฒŒ ์ƒ๋‹ดํ•ด๋ณด์„ธ์š”.
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    ์•ˆ๋…•ํ•˜์„ธ์š”. ํ•ดํ”ผ์บ ํผ์Šค AI ์ฑ—๋ด‡์ž…๋‹ˆ๋‹ค. ๋ฌด์—‡์ด ๊ถ๊ธˆํ•˜์‹ ๊ฐ€์š”?
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