Contribute to our special issue on The impact of interface design for soliciting user’s feedback
摘要截稿: 2018-01-30
全文截稿: 2018-04-28
影响因子: 1.781
期刊难度:
CCF分类: C类
中科院JCR分区:
• 大类 : 管理学 - 4区
• 小类 : 计算机:控制论 - 4区
• 小类 : 人体工程学 - 4区
Overview
Users’ feedback is becoming more and more important in many different contexts of interaction, such as in recommender systems, social network, e-democracy, quantified-self, affective computing, and also in the IOT world. Most of these systems need user feedback for their proper working (i.e. recommender systems, affective computing based systems, reputation systems), or because is linked to their inner nature (e-democracy and social network systems), or for adapting their behaviour according to a specific user’s behaviour while using an object in the real or virtual world (IOT and user-adaptive systems).Hence stimulatingusers to provide explicit feedback becomes an important challenge, especially as users are reluctant to provide it and using and relying on implicit feedback has its limitations.
The excplit and/or implicit collection of users feedback (opinions, ratings, likes, physiological states, usage of virtual or tangible objects, etc.) is a central feature in the the design of such systems, and their design may have an impact on the way the feedback is collected and interpreted.
The proposed special issue will focus on the impact of users’ feedback and on how feedback is solicited and ways to encourage/convince users to provide it.
What can I contribute?
- Rating scales and their design and evaluation
- Micro actionand their design and evaluation
- Evaluation of the use of tags, like, emoticons, icons
- Gamified approaches for eliciting users feedback
- Feedback elicitation in Quantified-self context
- What impacts user feedback in social network
- What impacts user feedback in IOT, expecially in the term of physical interaction
- What impacts user feedback in recommender systems
- What impacts user feedback in the ubiquitous web
- What impacts user feedback in the augmented reality
- Implict modalities for acquiring user feedback: user observation and monitoring, gaze and gesture detection, emotion detection, phisiological state detection etc
- Influence of interaction modalities (e.g. the rating scales widget, the use of gestures, etc) on the ratings