Presenting and visualizing image results for professional image searchers: A field evaluation

Göker, Ayşe; Butterworth, Richard; MacFarlane, Andy; Stumpf, Simone

doi:10.14236/ewic/hci2017.6

Cited by 2 publications

(2 citation statements)

References 9 publications

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“…the ability to pan and zoom images as suggested in section 6. We report this work in the same volume (Göker et al, 2017). A further area of fruitful research would be to examine cultural differences for example many Asian languages are pictorial in character (e.g.…”

Section: Discussionmentioning

confidence: 99%

Presenting and visualizing results on an image retrieval user interface

Göker

Butterworth

MacFarlane

et al. 2017

Electronic Workshops in Computing

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The volume of images available online has increased significantly but the choices offered by image retrieval systems have not kept pace. We describe the design and evaluation of a 'high density' image search interface focusing on the results pages. We quantitatively and qualitatively compared image presentation on a high density interface with a traditional image search interface. Our results show that users had major problems with high-density interfaces for images due to information overload. We point to further work which could improve the user experience.

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Section: Discussionmentioning

confidence: 99%

Presenting and visualizing results on an image retrieval user interface

Göker

Butterworth

MacFarlane

et al. 2017

Electronic Workshops in Computing

Self Cite

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“…Researchers working in the first of these areas have identified that Google or Google Image were the most frequently used tools to search for images among college students (Yoon, 2011). Some researchers worked on designing a high-density image search interface for creative professionals, such as journalists and copywriters (Göker et al , 2016). There are three types of user intentions – including explore/learn, entertain, and locate/acquire – dealing with image search behaviour (Xie et al , 2018).…”

Section: Literature Reviewmentioning

confidence: 99%

Image needs on social Q&A sites: a comparison of Zhihu and Baidu Zhidao

Deng¹,

Zhao

Huang

et al. 2019

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Purpose This study aims to examine why users search for images, how users describe their image needs and what the images are used for by analysing questions obtained from two Chinese social Q&A sites, Zhihu and Baidu Zhidao. Design/methodology/approach A total of 1,402 image questions were collected from Zhihu and Baidu Zhidao. Both quantitative analysis and qualitative content analysis were performed to identify user image needs and the potential differences on the two social Q&A sites. Findings Question-asker’s intention varies in different platforms. Zhihu users asked questions mainly aiming at a promotion of subsequent discussion, whereas users of Baidu Zhidao often did so to seek information. Syntactic attributes were not frequently used in both two sites. Zhihu users were more likely to express subjective evaluations on images (concept, emotion, theme and style) in their questions than users of Baidu Zhidao. In contrast, questions from Baidu Zhidao showed a tendency to more frequently include descriptive metadata (rights, format, size, quality and authenticity) and semantic attributes (generic activity, specific people, fashion and text) of the images than questions from Zhihu. Learning was an important use on social Q&A sites, especially on Baidu Zhidao. In addition, the images were primarily used to trigger emotion or served a persuasive purpose in Zhihu. Practical implications This study contributes to a better understanding of user image search behaviour, and the findings could be used to develop better image services on social Q&A sites. Meanwhile, the image attributes extracted from the questions are conducive to the improvement of image retrieval systems. Originality/value This study explored the features of image needs on social Q&A sites, especially considering image use specified in the question. The difference of image needs between two Chinese social Q&A sites (Zhihu and Baidu Zhidao) was identified.

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Presenting and visualizing image results for professional image searchers: A field evaluation

Cited by 2 publications

References 9 publications

Presenting and visualizing results on an image retrieval user interface

Presenting and visualizing results on an image retrieval user interface

Image needs on social Q&A sites: a comparison of Zhihu and Baidu Zhidao

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