网页浏览任务的用户情感测量模型研究
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摘要
采用实验与问卷调查相结合的研究方法探索了基于眼动技术的情感测量方法。首先采用问卷调查与专家访谈的形式设定了实验网站和实验任务;然后通过中文版PAD情感量表实验获得不同网站浏览任务下的被试情感状态,同时记录对应的眼动数据,将情感类别作为影响因素对记录的眼动数据进行单因素方差分析,选出与情感变化有关的眼动指标;最后,采用偏最小二乘回归方式建立眼动指标与情感值之间的关系模型。模型分析结果显示该情感预测模型能较好地预测浏览任务下被试情感状态,具有较好的适应性。
In this paper,experimental and survey research methods have been used to explore the emotion measurement methods based on eye tracking technology.At first,experimental websites and tasks are selected by the form of questionnaires and interviews with experts; Indeed,the emotional state of the subjects in the different websites and tasks is obtained with the PAD emotion scale of Chinese version.At the same time,the corresponding eye tracking data have been recorded;In the end,taking emotional categories as influencing factors,the single-factor analysis of variance of eye tracking data has been done,in order to select the eye tracking indicators which related to emotion and then using PLS to establish the model of eye tracking indicators and emotional values.The results showed that the emotional prediction model can play better prediction in the simple operational tasks with better adaptability.
In this paper,experimental and survey research methods have been used to explore the emotion measurement methods based on eye tracking technology.At first,experimental websites and tasks are selected by the form of questionnaires and interviews with experts; Indeed,the emotional state of the subjects in the different websites and tasks is obtained with the PAD emotion scale of Chinese version.At the same time,the corresponding eye tracking data have been recorded;In the end,taking emotional categories as influencing factors,the single-factor analysis of variance of eye tracking data has been done,in order to select the eye tracking indicators which related to emotion and then using PLS to establish the model of eye tracking indicators and emotional values.The results showed that the emotional prediction model can play better prediction in the simple operational tasks with better adaptability.
引文
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[2]袁科伟.情感计算在可用性测试中应用的研究[D].北京:北京邮电大学自动化学院,2009.
[3]Nyklicek I,Thayer J F,Van Doomen L J P.Cardio respiratory differentiation of Musically-induced emotions[J].Journal of Psychophysiology,1997,11(4):304-321.
[4]李建平,张平,王丽芳等.5种基本情绪自主神经反应模式特异性的实验研究[J].中国行为医学科学,2005,14(3):257-259.
[5]Yusoff N M,Salim S S.Scout and Affective Interaction Design:Evaluating Physiological Signals for Usability in Emotional[C].Processing ICCET2010,Chengdu,China,2010: 201-205.
[6]李强,侯艳红,苗丹民,廖明敏,王伟.不同情绪模式图片眼动特征的研究[J].中国行为医学科学,2006,15(1z):1121-1122.
[7]石金富,曹晓华,王钢,瞿彬.网页布局对视觉搜索影响的眼动研究[J].人类工效学,2008,14(4):1-3.
[8]梁贤英,王丹,许远理.情感测量研究现状与展望[J].长沙师范??专科学校学报,2010,4(3):35-37.
[9]Darwin C.The expression of the emotions in man and animals [M].ChicagO:The University of Chicago Press,1965.
[10]孙瑞山,陈农田.眼动分析技术及其在航空领域的应用进展[J].中国民航法学学报,2009,27(4):1-3.
[11]程时伟,孙守迁.手机用户界面可用性评估的眼动模型,第四届和谐人机环境联合学术会议论文集[C].北京:清华大学出版社,2008.
[12]Young L,Sheena.D Methods & designs:survey of eye movement recording methods[J].Behavior Research Methods & Instrumentation,1975:7(5):397-429.
[13]黄向阳,谢邦昌.统计学方法与应用[M].北京:中国人民大学出版社,2009.
[14]许凤华.偏最小二乘回归分析中若干问题的研究[D].青岛:山东科技大学信息科学与工程学院,2006.