Ubiquitous technologies such as mobile software applications (mobile apps) have a tremendous influence on the evolution of the social, cultural, economic, and political facets of life in society. Mobile apps fulfil many practical purposes for users including entertainment, transportation, financial management, etc. Given the ubiquity of mobile apps in the lives of individuals and the consequent effect of these technologies on society, it is essential to consider the relationship between human values and the development and deployment of mobile apps. The many negative consequences of violating human values such as privacy, fairness or social justice by technology have been documented in recent times. If we can detect these violations in a timely manner, developers can look to better address them. To understand the violation of human values in a range of common mobile apps, we analysed 22,119 app reviews from Google Play Store using natural language processing techniques. We base our values violation detection approach on a widely accepted model of human values; the Schwartz theory of basic human values. The results of our analysis show that 26.5% of the reviews contained text indicating user perceived violations of human values. We found that benevolence and self-direction were the most violated value categories, and conformity and tradition were the least violated categories. Our results also highlight the need for a proactive approach to the alignment of values amongst stakeholders and the use of app reviews as a valuable additional source for mining values requirements.
翻译:移动应用软件(移动应用程序)等移动软件应用(移动应用程序)对社会生活的社会、文化、经济和政治层面的演变有着巨大影响。移动应用程序满足了用户的许多实用目的,包括娱乐、交通、金融管理等。鉴于移动应用程序在个人生活中的普遍存在,以及这些技术对社会的影响,必须考虑人类价值观与发展和应用移动应用程序之间的关系。最近记录了技术侵犯人类价值观(如隐私、公平或社会正义)的许多消极后果。如果我们能够及时发现这些违法行为,开发商可以寻求更好地解决这些问题。为了了解在一系列通用移动应用程序中违反人类价值观的行为,我们用自然语言处理技术分析了Google Play Store的22 119个应用审查。我们以广泛接受的人类价值观模式为基础,根据Schwartzt人类基本价值观理论,我们的分析结果表明,26.5%的审查中含有表明用户认为违反人类价值观的文本。我们发现,对于各种共同的移动应用程序来说,开发商们可以寻找更好的解决方案。为了了解在一系列通用移动应用程序中违反人类价值观的行为,我们分析了22,119个应用程序的审查结果。我们用一种最不受侵犯的分类,因此需要先变整。