DISSERTATION ABSTRACT

Exploring Strategies to Prevent Harm fromWeb Search
Steven Zimmermanszimme@essex.ac.ukAbstract

Web search, the process of seeking and finding information online, is an ubiquitous activity engrained in the lives of many individuals and much of broader society. This activity, which hasbrought many benefits to individuals and society, has also opened the door to many harms, suchas echo chambers, loss of privacy and exposure to misinformation. Members of the information
retrieval (IR) community now recognize the dangers of the search technologies commonplace inour daily lives. The upshot of this recognition are growing efforts to address these dangers by
the IR community. These efforts focus heavily on system oriented solutions, but give limited
focus on behavioural and cognitive biases and behaviours of the search and even less attention tointerventions designed to address these biases and behaviours. As such, a theoretical framework
is proposed, with behavioural and cognitive strategies as a core component of interactive Web
search environments designed to minimize harm.
Using the framework as the foundation, this thesis presents a number of offline and online
studies to evaluate nudging, a popular intervention strategy rooted in the field of behavioural
economics, and boosting, a successful intervention strategy from the cognitive sciences, as strategies
to reduce risk of harm in Web search. The key takeaway from these studies being that bothboosting and nudging should be considered as viable approaches for harm prevention in Web search
environments, in addition to pure system and algorithmic solutions. Additional contributions of
this thesis include methods of study design for the comparison of multiple paradigms that promote
improved decision making, along with a set of evaluation metrics to measure the success of theIR system and user performance as they relate to the harms being prevented. Future research isneeded to confirm the effectiveness of these strategies for other types of harms.
Awarded by: University of Essex, Colchester, England on February 24th 2021.
Supervised by: Udo Kruschwitz, Jon Chamberlain and Chris Fox.
Available at: http://repository.essex.ac.uk/29762/.

ACM SIGIR Forum1Vol. 55 No. 1 - June 2021

Selected Publications
Steven Zimmerman, Chris Fox, and Udo Kruschwitz. Improving hate speech detection with deeplearning ensembles. In Proceedings of the 10th International Conference on Language Resourcesand Evaluation, LREC 2018, 2018. URL https://www.aclweb.org/anthology/L18-1404.pdf.
Steven Zimmerman, Alistair Thorpe, Chris Fox, and Udo Kruschwitz. Investigating the interplay
between searchers’ privacy concerns and their search behavior. In Proceedings of the 42ndInternational ACM SIGIR Conference on Research and Development in Information Retrieval,
SIGIR’19, pages 953–956. ACM, 2019a. URL https://dl.acm.org/doi/10.1145/3331184.
3331280.
Steven Zimmerman, Alistair Thorpe, Chris Fox, and Udo Kruschwitz. Privacy nudging in search:
Investigating potential impacts. In Proceedings of the 2019 Conference on Human Information
Interaction and Retrieval, CHIIR ’19, pages 283–287, 2019b. URL https://dl.acm.org/doi/10.1145/3295750.3298952.
Steven Zimmerman, Stefan Herzog, David Elsweiler, Jon Chamberlain, and Udo Kruschwitz.
Towards a framework for harm prevention in web search. In Bridging the Gap between Information Science, Information Retrieval and Data Science - BIRDS, 2020a. URL https://birds-ws.github.io/birds2020/assets/papers/BIRDS2020_zImmerman.pdf.
Steven Zimmerman, Alistair Thorpe, Jon Chamberlain, and Udo Kruschwitz. Towards searchstrategies for better privacy and information. In Proceedings of the 2020 Conference on HumanInformation Interaction and Retrieval, CHIIR ’20, pages 124–134, 2020b. URL https://dl.
acm.org/doi/10.1145/3343413.3377958.

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