Towards Exploring User Perception of a Privacy Sensitive Information Detection Tool

Bracamonte, Vanessa; Tesfay, Welderufael B.; Kiyomoto, Shinsaku

doi:10.5220/0010319706280634

Cited by 8 publications

(8 citation statements)

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“…To the best of our knowledge, there is not much research about privacy concerns on privacy enhancing tools for social media. Closest to our work is the study by Bracamonte et al [5], who evaluated user perception of a privacy tool for social media text, and found that privacy concern was a frequent theme of users' negative opinion about the tool. In a follow up study [4], performance expectancy (usefulness), social influence and perception of accuracy were found to be positively and privacy concerns about the tool and privacy self-efficacy were found to be negatively associated with user intentions to use a privacy sensitive information detection tool.…”

Section: Related Workmentioning

confidence: 82%

“…There is some research on the perception of users towards different aspects of privacy enhancing tools [24], but research on privacy tools that process text and image data do not often include evaluation of users' privacy concerns towards the tool itself. Bracamonte et al [4,5] report that privacy concerns have a negative effect on intention of using privacy tools that process users' social media posts.…”

Section: Introductionmentioning

confidence: 99%

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“All apps do this”: Comparing Privacy Concerns Towards Privacy Tools and Non-Privacy Tools for Social Media Content

Bracamonte

Pape

Loebner

2022

PoPETs

Self Cite

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Users report that they have regretted accidentally sharing personal information on social media. There have been proposals to help protect the privacy of these users, by providing tools which analyze text or images and detect personal information or privacy disclosure with the objective to alert the user of a privacy risk and transform the content. However, these proposals rely on having access to users’ data and users have reported that they have privacy concerns about the tools themselves. In this study, we investigate whether these privacy concerns are unique to privacy tools or whether they are comparable to privacy concerns about non-privacy tools that also process personal information. We conduct a user experiment to compare the level of privacy concern towards privacy tools and nonprivacy tools for text and image content, qualitatively analyze the reason for those privacy concerns, and evaluate which assurances are perceived to reduce that concern. The results show privacy tools are at a disadvantage: participants have a higher level of privacy concern about being surveilled by the privacy tools, and the same level concern about intrusion and secondary use of their personal information compared to non-privacy tools. In addition, the reasons for these concerns and assurances that are perceived to reduce privacy concern are also similar. We discuss what these results mean for the development of privacy tools that process user content.

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Section: Related Workmentioning

confidence: 82%

Section: Introductionmentioning

confidence: 99%

“All apps do this”: Comparing Privacy Concerns Towards Privacy Tools and Non-Privacy Tools for Social Media Content

Bracamonte

Pape

Loebner

2022

PoPETs

Self Cite

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“…Several tools have been developed to inform users in decision-making on privacy issues. Bracamonte et al [24] refers to detectors of privacy-sensitive information. Detecting such information requires some ontology on privacy, e.g., as proposed by Li et al [12], and leads to alerts that trigger decisions on user privacy.…”

Section: Facilitating User Engagementmentioning

confidence: 99%

Motivating Users to Manage Privacy Concerns in Cyber-Physical Settings—A Design Science Approach Considering Self-Determination Theory

Oppl

Stary

2022

Sustainability

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Connectivity is key to the latest technologies propagating into everyday life. Cyber-Physical Systems (CPS) and Internet-of-Things (IoT) applications enable users, machines, and technologically enriched objects (‘Things’) to sense, communicate, and interact with their environment. Albeit making human beings’ lives more comfortable, these systems collect huge quantities of data that may affect human privacy and their digital sovereignty. Engaging in control over individuals by digital means, the data and the artefacts that process privacy-relevant data can be addressed by Self-Determination Theory (SDT) and its established instruments. In this paper, we discuss how the theory and its methodological knowledge can be considered for user-centric privacy management. We set the stage for studying motivational factors to improve user engagement in identifying privacy needs and preserving privacy when utilizing or aiming to adapt CPS or IoT applications according to their privacy needs. SDT considers user autonomy, self-perceived competence, and social relatedness relevant for human engagement. Embodying these factors into a Design Science-based CPS development framework could help to motivate users to articulate privacy needs and adopt cyber-physical technologies for personal task accomplishment.

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“…Since its introduction by Nobel Prize winners Richard Thaler and Cass Sunstein, the "nudge" theory has been extensively investigated and applied repeatedly to the design of privacy-enhancing technologies. When it comes to OSNs, there is a wide variety of privacy nudges in the current literature whose goal is to support users' online self-disclosure decisions [7,9,10,16,30,38]. For instance, Raber et al [38] introduced PrivacyWedges, a visualization strategy for aiding the audience selection of social media publications.…”

Section: Background and Related Workmentioning

confidence: 99%

“…Such is the case of Botti-Cebriá et al [9], who applied a compound of Natural Language Processing (NLP) techniques for determining whether a post contains information about one's location, health, and personal identifiers, among others. In line with this, Bracamonte et al [10] empirically assessed users' perception of warnings about the presence of personal information in their posts. All in all, most study participants considered such nudges useful but were agnostic regarding their future adoption.…”

Section: Background and Related Workmentioning

confidence: 99%

ENAGRAM: An App to Evaluate Preventative Nudges for Instagram

Ferreyra,

Ostendorf,

Aïmeur

et al. 2022

Preprint

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Online self-disclosure is perhaps one of the last decade's most studied communication processes, thanks to the introduction of Online Social Networks (OSNs) like Facebook. Self-disclosure research has contributed significantly to the design of preventative nudges seeking to support and guide users when revealing private information in OSNs. Still, assessing the effectiveness of these solutions is often challenging since changing or modifying the choice architecture of OSN platforms is practically unfeasible. In turn, the effectiveness of numerous nudging designs is supported primarily by self-reported data instead of actual behavioral information. Objective: This work presents ENAGRAM, an app for evaluating preventative nudges, and reports the first results of an empirical study conducted with it. Such a study aims to showcase how the app (and the data collected with it) can be leveraged to assess the effectiveness of a particular nudging approach. Method: We used ENAGRAM as a vehicle to test a risk-based strategy for nudging the self-disclosure decisions of Instagram users. For this, we created two variations of the same nudge (i.e., with and without risk information) and tested it in a between-subjects experimental setting. Study participants (N=22) were recruited via Prolific and asked to use the app regularly for 7 days. An online survey was distributed at the end of the experiment to measure some privacy-related constructs. Results: From the data collected with ENAGRAM, we observed lower (though non-significant) self-disclosure levels when applying risk-based interventions. The constructs measured with the survey were not significant either, except for participants' External Information Privacy Concerns (EIPC). Implications: Our results suggest that (i) ENAGRAM is a suitable alternative for conducting longitudinal experiments in a privacy-friendly way, and (ii) it provides a flexible framework for the evaluation of a broad spectrum of nudging solutions.

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Towards Exploring User Perception of a Privacy Sensitive Information Detection Tool

Cited by 8 publications

References 0 publications

“All apps do this”: Comparing Privacy Concerns Towards Privacy Tools and Non-Privacy Tools for Social Media Content

“All apps do this”: Comparing Privacy Concerns Towards Privacy Tools and Non-Privacy Tools for Social Media Content

Motivating Users to Manage Privacy Concerns in Cyber-Physical Settings—A Design Science Approach Considering Self-Determination Theory

ENAGRAM: An App to Evaluate Preventative Nudges for Instagram

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