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| Chinese Web users' daily image needs and seeking behavior in a Q&A community | |
| HUANG Kun1; NIU Xi2; WANG Shanshan1; WANG Kaifei1; Kun Huang(Email:huangkun@bnu.edu.cn) | |
| 2015-03-24 | |
| Source Publication | Chinese Journal of Library and Information Science
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| Volume | 8Issue:1Pages:1-20 |
| Abstract | Purpose: In order to further the understanding of Chinese Web users' image-seeking behavior, this study explores the kinds of images that Chinese Web users seek online and how they express their requests. Design/methodology/approach: We used five pairs of simulated keywords to collect 893 image-seeking questions from Baidu Zhidao. Then, we revised the subject category of questions to analyze popular image needs. In addition, we conducted content analysis and descriptive statistical analysis to identify image-seeking motivations and image features used in the requests in terms of the two theories of image feature classification and image use. Findings: Among the 893 questions, the image searches for entertainment accounted for 47.59%, more than the searches for professional knowledge (37.40%) and personal daily activities (15.01%). With regard to motivation, over 60% of the questions were identified as used for learning, which is well over the proportion of questions used for illustrating. Thus, these questions requested images as sources of data rather than sources of objects. Non-visual features (47.58%) were used most frequently in question descriptions, slightly higher than semantic features (45.96%). Users who lacked domain knowledge tended to use general words rather than specific words to describe their requests. However, not many users used syntactic features when seeking images. Nevertheless, most of the users had a fairly clear idea about what the target image should look like. Research limitations: We studied only one question and answer (Q&A) community using five pairs of simulated keywords. Practical implications: The findings should be helpful in strengthening the functionality of Q&A systems, promoting the theories of image feature classification, and shedding light on information literacy training.
Originality/value: This study is one of the first research efforts that discusses Chinese Web users' daily image searches and querying behavior in natural language in a Q&A community, which should help to further the understanding of the principles of image-seeking behavior among Chinese Web users. ; Purpose: In order to further the understanding of Chinese Web users' image-seeking behavior, this study explores the kinds of images that Chinese Web users seek online and how they express their requests.Design/methodology/approach: We used five pairs of simulated keywords to collect 893 image-seeking questions from Baidu Zhidao. Then, we revised the subject category of questions to analyze popular image needs. In addition, we conducted content analysis and descriptive statistical analysis to identify image-seeking motivations and image features used in the requests in terms of the two theories of image feature classification and image use. Findings: Among the 893 questions, the image searches for entertainment accounted for 47.59%, more than the searches for professional knowledge (37.40%) and personal daily activities (15.01%). With regard to motivation, over 60% of the questions were identified as used for learning, which is well over the proportion of questions used for illustrating. Thus, these questions requested images as sources of data rather than sources of objects. Non-visual features (47.58%) were used most frequently in question descriptions, slightly higher than semantic features (45.96%). Users who lacked domain knowledge tended to use general words rather than specific words to describe their requests. However, not many users used syntactic features when seeking images. Nevertheless, most of the users had a fairly clear idea about what the target image should look like. Research limitations: We studied only one question and answer (Q&A) community using five pairs of simulated keywords. Practical implications: The findings should be helpful in strengthening the functionality of Q&A systems, promoting the theories of image feature classification, and shedding light on information literacy training.
Originality/value: This study is one of the first research efforts that discusses Chinese Web users' daily image searches and querying behavior in natural language in a Q&A community, which should help to further the understanding of the principles of image-seeking behavior among Chinese Web users. |
| Subtype | Research Papers |
| Keyword | Image Needs Image Seeking Baidu Zhidao q&a Communities Image Users |
| Subject Area | 新闻学与传播学 ; 图书馆、情报与文献学 |
| URL | 查看原文 |
| Indexed By | 其他 |
| Project Number | Grant No.: 11YJC870010 |
| Language | 英语 |
| Funding Organization | This work is supported by Humanities and Social Science Fund from the Chinese Ministry of Education (Grant No.: 11YJC870010). |
| Document Type | 期刊论文 |
| Identifier | http://ir.las.ac.cn/handle/12502/7662 |
| Collection | Journal of Data and Information Science_Chinese Journal of Library and Information Science-2015 |
| Corresponding Author | Kun Huang(Email:huangkun@bnu.edu.cn) |
| Affiliation | 1.School of Government, Beijing Normal University, Beijing 100875, China 2.School of Informatics and Computing, Indiana University at Indianapolis, Indianapolis, IN 46202, USA |
| First Author Affilication | 中国科学院文献情报中心 |
| Recommended Citation GB/T 7714 | HUANG Kun,NIU Xi,WANG Shanshan,et al. Chinese Web users' daily image needs and seeking behavior in a Q&A community[J]. Chinese Journal of Library and Information Science,2015,8(1):1-20. |
| APA | HUANG Kun,NIU Xi,WANG Shanshan,WANG Kaifei,&Kun Huang.(2015).Chinese Web users' daily image needs and seeking behavior in a Q&A community.Chinese Journal of Library and Information Science,8(1),1-20. |
| MLA | HUANG Kun,et al."Chinese Web users' daily image needs and seeking behavior in a Q&A community".Chinese Journal of Library and Information Science 8.1(2015):1-20. |
| Files in This Item: | Download All | |||||
| File Name/Size | DocType | Version | Access | License | ||
| 20150101.pdf（5172KB） | 期刊论文 | 出版稿 | 开放获取 | CC BY-NC-ND | View Download | |
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