Enabling Customization of Discussion Forums for Blind Users

被引:1
作者
Sunkara M. [1 ]
Prakash Y. [1 ]
Lee H.-N. [2 ]
Jayarathna S. [1 ]
Ashok V. [1 ]
机构
[1] Old Dominion University, Norfolk, VA
[2] Stony Brook University, Stony Brook, NY
关键词
assistive technology; blind; online discussion forum; screen reader;
D O I
10.1145/3593228
中图分类号
学科分类号
摘要
Online discussion forums have become an integral component of news, entertainment, information, and video-streaming websites, where people all over the world actively engage in discussions on a wide range of topics including politics, sports, music, business, health, and world affairs. Yet, little is known about their usability for blind users, who aurally interact with the forum conversations using screen reader assistive technology. In an interview study, blind users stated that they often had an arduous and frustrating interaction experience while consuming conversation threads, mainly due to the highly redundant content and the absence of customization options to selectively view portions of the conversations. As an initial step towards addressing these usability concerns, we designed PView - a browser extension that enables blind users to customize the content of forum threads in real time as they interact with these threads. Specifically, PView allows the blind users to explicitly hide any post that is irrelevant to them, and then PView automatically detects and filters out all subsequent posts that are substantially similar to the hidden post in real time, before the users navigate to those portions of the thread. In a user study with blind participants, we observed that compared to the status quo, PView significantly improved the usability, workload, and satisfaction of the participants while interacting with the forums. © 2023 Owner/Author.
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  • [1] Abascal J., Arrue M., Valencia X., Tools for web accessibility evaluation, Web accessibility: a foundation for research, pp. 479-503, (2019)
  • [2] Aghakhani H., Machiry A., Nilizadeh S., Kruegel C., Vigna G., Detecting deceptive reviews using generative adversarial networks, 2018 IEEE Security and Privacy Workshops (SPW), pp. 89-95, (2018)
  • [3] Agrawal A., An A., Affective representations for sarcasm detection, The 41st International ACM SIGIR Conference on Research & Development in Information Retrieval, pp. 1029-1032, (2018)
  • [4] Ahmad M., Junus K., Santoso H.B., Automatic content analysis of asynchronous discussion forum transcripts: A systematic literature review, Education and Information Technologies, 2022, pp. 1-56, (2022)
  • [5] Akcaoglu M., Lee E., Increasing social presence in online learning through small group discussions, International Review of Research in Open and Distributed Learning, 17, 3, pp. 1-17, (2016)
  • [6] Andronico P., Buzzi M., Castillo C., Leporini B., Improving search engine interfaces for blind users: a case study, Universal Access in the Information Society, 5, 1, pp. 23-40, (2006)
  • [7] VoiceOver, (2023)
  • [8] Ashok V., Borodin Y., Stoyanchev S., Puzis Y., Ramakrishnan I.V., Wizard-of-Oz evaluation of speech-driven web browsing interface for people with vision impairments, Proceedings of the 11th Web for All Conference, pp. 1-9, (2014)
  • [9] Ashok V., Puzis Y., Borodin Y., Ramakrishnan I.V., Web screen reading automation assistance using semantic abstraction, Proceedings of the 22nd International Conference on Intelligent User Interfaces, pp. 407-418, (2017)
  • [10] Aydin A.S., Feiz S., Ashok V., Ramakrishnan I.V., Towards making videos accessible for low vision screen magnifier users, Proceedings of the 25th international conference on intelligent user interfaces, pp. 10-21, (2020)