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数据分析与知识发现  2017, Vol. 1 Issue (5): 42-51     https://doi.org/10.11925/infotech.2096-3467.2017.05.06
  专题 本期目录 | 过刊浏览 | 高级检索 |
用户步行导航过程中的情感变化研究*
吴丹(), 刘畅, 李翼
武汉大学信息管理学院 武汉 430072
Changing Sentiments of Pedestrian Navigation System Users
Wu Dan(), Liu Chang, Li Yi
School of Information Management, Wuhan University, Wuhan 430072, China
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摘要 

目的】优化用户体验, 提高用户对导航系统的持续使用性。【方法】采用用户实验和基于情感词典的情感分析方法, 使用程度副词系数量、中文情感词汇本体、极性短语的强度计算公式等对情感短语进行量化, 分析影响情感的因素及其变化规律。【结果】用户在步行导航过程中的情感变化主要受到系统因素和环境因素的影响, 系统更新的不及时、定位不准、环境恶劣均会对用户的情感造成影响。【局限】情感是一个复杂而且涵盖广泛的概念, 仅通过文本分析可能存在不足。【结论】通过改进系统本身和增添人性化的设置提高用户对导航系统的持续使用性, 为系统未来的升级提供有效参考。

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吴丹
刘畅
李翼
关键词 步行导航情感变化情感词汇本体极性短语情感强度计算    
Abstract

[Objective] This paper aims to optimize user experience and keep them using the pedestrian navigation system. [Methods] First, we collected data from an experiment with 30 participants. Then we conducted analysis with the help of sentiment dictionaries. Finally, we obtained influencing factors and their changing patterns with the number of degree adverbs, Chinese sentiment vocabulary Ontology and degree-calculating formula of polar phrases. [Results] We found that users’ sentiment changed due to the systematic and environmental factors. Untimely system updates, inaccurate locations and tough environment all posed negative effects to the user’s sentiments. [Limitations] Text analysis could not study the sentiments comprehensively. [Conclusions] We could optimize user experience by improving system design and adding user-friendly features, which provides direction for future developments.

Key wordsPedestrian Navigation    Sentiment Change    Sentiment Vocabulary Ontology    Polar Phrase    Emotional Intensity Calculation
收稿日期: 2017-02-08      出版日期: 2017-06-06
ZTFLH:  G250  
基金资助:*本文系武汉大学自主科研项目(人文社会科学)“人机交互与协作创新团队”(项目编号: Whu2016020)的研究成果之一
引用本文:   
吴丹, 刘畅, 李翼. 用户步行导航过程中的情感变化研究*[J]. 数据分析与知识发现, 2017, 1(5): 42-51.
Wu Dan,Liu Chang,Li Yi. Changing Sentiments of Pedestrian Navigation System Users. Data Analysis and Knowledge Discovery, 2017, 1(5): 42-51.
链接本文:  
http://manu44.magtech.com.cn/Jwk_infotech_wk3/CN/10.11925/infotech.2096-3467.2017.05.06      或      http://manu44.magtech.com.cn/Jwk_infotech_wk3/CN/Y2017/V1/I5/42
量级 相对程度副词 绝对程度副词 系数量
极量 太、完全、爆炸、超级 1
高量 更、越 很、非常、特别、十分、好、
蛮、真、挺
0.75
中量 较、比较、
还、没有…
想象的
不大、不太、不很、没有太、
没怎么、不是非常、没有非常、
不是特别、不是那么、没那么
0.5
低量 稍、略、…
一些
有点、有些、一点、一点点 0.25
  程度副词分类表
极性短语 强度计算公式 例句 强度
S=PW E(PW) 天气凉快 3
S=NA+PW E(PW)×E(NA) 天气不凉快 -2.4
S=NA+NA+PW E(PW)×E(NA)×E(NA) 天气不是不凉快 1.92
S=DA+PW E(PW)+[(1-E(PW))×L(DA)
若PW是正面的
E(PW)+[-1-E(PW)]×L(DA)
若PW是负面的
天气比较凉快

路上很堵
2

-2
  极性短语的极性计算
短语极性 频次 频率 强度值
正向 52 19.92% 140
负向 95 36.40% 323.5
中性 114 43.68% 311.15
合计 261 100.00% 774.65
  短语极性的统计
情感大类 情感类 例词 频次 频次合计 频率 强度值 强度值合计 占总强度值之比
快乐 高兴、愉悦、顺利、轻松 18 21 8% 53.5 59 8%
安心 平静 3 5.5
尊敬 63 24% 194 25%
赞扬 准确、及时、良好、快速 58 149
相信 确定 5 45
喜爱
祝愿
愤怒 投诉 1 1 0% 7 7 1%
悲伤 漫长、风吹日晒、饥肠辘辘 35 38 15% 98.8 106.8 14%
失望 绝望、无语、招架不住 3 8
急躁 4 8 3% 12.6 18.6 2%
恐惧 惊吓、困难 4 6
烦闷 烦躁、心烦、疲劳、闷郁 21 129 49% 65.5 387 50%
憎恶 讨厌、麻烦、不快 7 16.25
贬责 炎热、阻塞、绕圈子、偏差 98 280.25
妒忌
怀疑 怀疑 3 25
惊奇 奇特 1 1 0% 2.25 2.25 0%
  情感类短语的统计
  正负向情感的变化
  7大类情感短语频次
  7大类情感的变化
  主客观正负向情感变化的对比
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