바로가기메뉴

본문 바로가기 주메뉴 바로가기

logo

  • P-ISSN1225-598X

검색 언어가 웹 정보검색행위에 미치는 영향에 관한 연구- 웹 정보검색행위의 양상 차이를 중심으로 -

A Study on the Effects of Search Language on Web Searching Behavior: Focused on the Differences of Web Searching Pattern

한국문헌정보학회지, (P)1225-598X;
2018, v.52 no.3, pp.289-334
https://doi.org/10.4275/KSLIS.2018.52.3.289
변제연 (성균관대학교 정보관리연구소)
  • 다운로드 수
  • 조회수

초록

웹상에서 영어 이외의 언어들로 이루어진 정보가 빠르게 증가하고 있지만, 여전히 영어 정보가 가장 큰 비중을 차지함에 따라 공통어(lingua franca)로서의 지배적인 영향을 미치고 있다. 따라서 영어가 비모어인 이용자들이 보다 다양하고 풍부한 정보를 획득할 수 있도록 하기 위해서는 비영어권 화자의 모어 정보검색행위와 영어 정보검색행위에 대한 조사를 통해 주요 특징 및 차이점을 살펴볼 필요가 있다. 본 연구에서는 국내 한 사립대학의 대학생 24명을 대상으로 동시적 사고구술 기법을 적용한 정보검색 실험을 실시해 한글 정보검색행위 및 영어 정보검색행위와 인지과정을 조사하였다. 관찰데이터 및 사고구술데이터의 정성적 데이터를 기반으로, 검색 언어에 따른 웹 정보검색행위의 양상 차이에 대한 빈도분석을 실시하였다. 연구 결과, 한글 검색에서 능동적이고 적극적이며 독립적인 특성의 양상이, 영어 검색에서 수동적이고 소극적이며 의존적인 특성의 양상이 나타났다. 한글 검색에서는 이용자, 태스크, 시스템 등 다양한 출처에서 용어를 추출·조합한 검색어 구성, 여러 수준에서의 검색범위 조정, 검색엔진 검색결과페이지 내 탐색 대상 아이템의 선택과 관련한 원활한 필터링, 다수 아이템의 탐색 및 비교, 웹 페이지의 전체 내용 브라우징 등이 주요 특징으로 확인되었다. 반면, 영어 검색에서는 주로 태스크 추출 용어 중심 검색어 구성, 제한된 검색범위 선호, 카테고리나 링크 등 아이템과 아이템 간 관련성에 의존한 탐색 대상 아이템 선택, 동일 아이템의 반복적 탐색, 웹 페이지의 일부 내용 브라우징, 그리고 사전 및 번역기와 같은 언어지원도구의 빈번한 사용 등이 두드러진 특징으로 파악되었다.

keywords
Search Language Web Searching Information Searching Behavior Think-Aloud Method 검색 언어 웹 정보검색 정보검색행위 사고구술 기법

Abstract

Even though information in many languages other than English is quickly increasing, English is still playing the role of the lingua franca and being accounted for the largest proportion on the web. Therefore, it is necessary to investigate the key features and differences between “information searching behavior using mother tongue as a search language” and “information searching behavior using English as a search language” of users who are non-mother tongue speakers of English to acquire more diverse and abundant information. This study conducted the experiment on the web searching which is applied in concurrent think-aloud method to examine the information searching behavior and the cognitive process in Korean search and English search through the twenty-four undergraduate students at a private university in South Korea. Based on the qualitative data, this study applied the frequency analysis to web search pattern under search language. As a result, it is active, aggressive and independent information searching behavior in Korean search, while information searching behavior in English search is passive, submissive and dependent. In Korean search, the main features are the query formulation by extract and combine the terms from various sources such as users, tasks and system, the search range adjustment in diverse level, the smooth filtering of the item selection in search engine results pages, the exploration and comparison of many items and the browsing of the overall contents of web pages. Whereas, in English search, the main features are the query formulation by the terms principally extracted from task, the search range adjustment in limitative level, the item selection by rely on the relevance between the items such as categories or links, the repetitive exploring on same item, the browsing of partial contents of web pages and the frequent use of language support tools like dictionaries or translators.

keywords
Search Language Web Searching Information Searching Behavior Think-Aloud Method 검색 언어 웹 정보검색 정보검색행위 사고구술 기법

참고문헌

1.

심원식, 안혜연, 변제연. 2015. 질의 언어 및 복잡성이 대학생의 웹 정보탐색에 미치는 영향에 관한연구. 한국문헌정보학회지, 49(2), 51-73.

2.

이경순. 2004. 한국어 정보처리: 한국어-영어/일본어-영어 교차언어 정보검색에서 클러스터 분석을 통한 성능 향상. 정보처리학회논문지 B, 11(2), 233-240.

3.

조연정. 2008. 『정음기호를 중간어로 한 한-중 교차검색어 엔진구성에 관한 연구』. 박사학위논문, 경희대학교 정보통신전문대학원.

4.

Amato, G. et al. 2007. MultiMatch - Multilingual/Multimedia Access to Cultural Heritage."Research and Advanced Technology for Digital Libraries, 4675, 505-508.

5.

Belkin, N. J. 1993. “Interaction with Texts: Information retrieval as information seeking behavior." In G. Knorz, J. Krause, & C. Womser-Hacker (Eds.), “Information Retrieval ’93:Von der Modellierung zur Anwendung." Konstanz: Universitaetsverlag Konstanz.

6.

Belkin, N. J. 1996. “Intelligent Information Retrieval: Whose Intelligence?" In J. Krause, M. Herfurth, and J. Marx (Eds). “Harausforderungen an Die Informationswirtschaft. Informationsverdichtung, Informationsbewertung und Datenvisualisierung." In Proceedings of the 5th International Symposium for Information Science (ISI ‘96), Konstanz: Universitätsverlag Konstanz.

7.

Belkin, N. J., Oddy, R. N., and Brooks, H. M. 1982. ASK for Information Retrieval: Part II. Results of a Design Study." Journal of Documentation, 38(3), 145-164.

8.

Berendt, B., and Kralisch, A. 2009. A User-centric Approach to Identifying Best Deployment Strategies for Language Tools: The Impact of Content and Access Language on Web User Behaviour and Attitudes." Information Retrieval, 12(3), 380-399.

9.

Bhattacharya, P., Goyal, P., and Sarkar, S. 2016. Using Word Embeddings for Query Translation for Hindi to English Cross Language Information Retrieval." arXiv preprint arXiv: 1608.01561.

10.

Borlund, P., and Ingwersen, P. 1997. The Development of a Method for the Evaluation of Interactive Information Retrieval Systems." Journal of Documentation, 53(3), 225-250.

11.

Chu, P. et al. 2012. “An Exploratory Study on Search Behavior in Different Languages."In Proceedings of the 4th Information Interaction in Context Symposium, New York: 318-321.

12.

Ericsson, K. A., and Simon, H. A. 1980. Verbal Reports as Data." Psychological Review, 87(3), 215.

13.

Gao, W. et al. 2007. “Cross-lingual Query Suggestion using Query Logs of Different Languages."In Proceedings of 30th International Conference on Research and Development in Information Retrieval (SIGIR): 463-470.

14.

Grefenstette, G. and Nioche, J. 2000. “Estimation of English and non-English Language Use on the WWW." In Content-Based Multimedia Information Access-Volume 1. LE CENTRE DE HAUTES ETUDES INTERNATIONALES D'INFORMATIQUE DOCUMENTAIRE.

15.

Ingwersen, P. 1992. Information Retrieval Interaction. London: Taylor Graham.

16.

Ingwersen, P. 1996. Cognitive Perspectives of Information Retrieval Interaction: Elements of a Cognitive IR Theory." Journal of Documentation, 52(1), 3-50.

17.

Ingwersen, P. 1999. Cognitive Information Retrieval." Annual Review of Information Science and Technology, 34, 3-52.

18.

Ingwersen, P. and Järvelin, K. 2005. The Turn: Integration of Information Seeking and Retrieval in Context. Heidelberg: Springer.

19.

Internet world Stats. 2017. Internet World Users by Language. [online] [cited 2017. 10. 25.]<http://www.internetworldstats.com/stats7.htm>

20.

Jones, G. et al. 2001. A Framework for Cross-language Information Access: Application to English and Japanese." Computers and the Humanities, 35(4), 371-388.

21.

Kralisch, A. and Berendt, B. 2004. “Linguistic Determinants of Search Behaviour on Websites."In Proceedings of the Fourth International Conference on Cultural Attitudes towards Technology and Communication, 27, Karlstad, Sweden.

22.

Kralisch, A., and Berendt, B. 2005. Language-sensitive Search Behaviour and the Role of Domain Knowledge." New Review of Hypermedia and Multimedia, 11(2), 221-246.

23.

Kralisch, A. and Mandl, T. 2006. “Barriers to Information Access Across Languages on the Internet: Network and Language Effects." In System Sciences, 2006. HICSS'06. In Proceedings of the 39th Annual Hawaii International Conference, 3. IEEE. Hawaii, United States.

24.

Kralisch, A., Yeo, A. W. and Jali, N. 2006. “Linguistic and Cultural Differences in Information Categorization and Their Impact on Website Use." In System Sciences, 2006. HICSS'06. In Proceedings of the 39th Annual Hawaii International Conference 5, IEEE. Hawaii, United States.

25.

McCarley, J. S. 1999. “Should We Translate the Documents or the Queries in Cross-language Information Retrieval?" In Proceedings of the 37th annual meeting of the Association for Computational Linguistics on Computational Linguistics, Association for Computational Linguistics.

26.

Nie, J.Y. 2010. Cross-Language Information Retrieval: Synthesis Lectures on Human Language Technologies. CA: Morgan and Claypool.

27.

Pecina, P. et al. 2014. Adaptation of Machine Translation for Multilingual Information Retrieval in the Medical Domain." Artificial Intelligence in Medicine, 61(3), 165-185.

28.

Peters, C. 2001. “Cross-Language Information Retrieval and Evaluation." Workshop of Cross-Language Evaluation Forum, CLEF 2000, Lisbon, Portugal, September 21-22, 2000, Revised Papers. Springer.

29.

Peters, C., Braschler, M. and Clough, P. 2012. Multilingual Information Retrieval: From Research To Practice. Springer Science & Business Media.

30.

Saracevic, T. 1997. “The Stratified Model of Information Retrieval Interaction: Extension and Applications." In Proceedings of the ASIS Annual Meeting, 34: 313-327.

31.

Singer, G., Norbisrath, U., and Lewandowski, D. 2012. Ordinary Search Engine Users Carrying out Complex Search Tasks. Journal of Information Science, 39(3), 346-358.

32.

Sonnenwald, D. H., Wildemuth, B. M., and Harmon, G. L. 2001. A Research Method to Investigate Information Seeking Using the Concept of Information Horizons: An Example from a Study of Lower Socio-economic Students' Information Seeking Behaviour. The New Review of Information Behaviour Research, 2, 65-86.

33.

Tu, Y. J. 2012. Information Search Behavior of ESL Users when Accessing Online Information in English: Using Taiwanese and Indonesian Students as an Example. M.A. thesis, Department of Industrial Management, National Taiwan University of Science and Technology.

34.

Vakkari, P. 2003. Task-based Information Searching." Annual Review of Information Science and Technology, 37(1), 413-464.

35.

Wilson, T. D. 1999. Models in Information Behavior Research. Journal of Documentation, 55(3), 249-270.

36.

World Wide Web Technology Surveys. 2017. Historical Yearly Trends in the Usage of Content Languages for Websites. [online] [cited 2017. 10. 25.]<https://w3techs.com/technologies/history_overview/content_language/ms/y>

37.

Xie, I. 2008. Interactive Information Retrieval in Digital Environments. Hershey·New York:IGI Global.

한국문헌정보학회지