•Inferential analytics may reinforce existing biases about gender stereotyping.•In a N = 109 pilot sample, 19% of Twitter users were misgendered.•Gender classifiers are binary and do not account for ...other than male/female gender categories.•LGBTQAI+ community members and straight women may be more often misgendered than straight men in social media.
Online and social media platforms employ automated recognition methods to presume user preferences, sensitive attributes such as race, gender, sexual orientation, and opinions. These opaque methods can predict behaviors for marketing purposes and influence behavior for profit, serving attention economics but also reinforcing existing biases such as gender stereotyping. Although two international human rights treaties include explicit obligations relating to harmful and wrongful stereotyping, these stereotypes persist online and offline. By identifying how inferential analytics may reinforce gender stereotyping and affect marginalized communities, opportunities for addressing these concerns and thereby increasing privacy, diversity, and inclusion online can be explored. This is important because misgendering reinforces gender stereotypes, accentuates gender binarism, undermines privacy and autonomy, and may cause feelings of rejection, impacting people's self-esteem, confidence, and authenticity. In turn, this may increase social stigmatization. This study brings into view concerns of discrimination and exacerbation of existing biases that online platforms continue to replicate and that literature starts to highlight. The implications of misgendering on Twitter are investigated to illustrate the impact of algorithmic bias on inadvertent privacy violations and reinforcement of social prejudices of gender through a multidisciplinary perspective, including legal, computer science, and critical feminist media-studies viewpoints. An online pilot survey was conducted to better understand how accurate Twitter's gender inferences of its users’ gender identities are. This served as a basis for exploring the implications of this social media practice.
•There are three aspects of our manuscript that we believe will attract general readers of your journal.•First, we propose a novel privacy-preserving real-time bidding protocol to protect the user’s ...data privacy, which to the best of our knowledge, is the first privacy preserving protocol in real-time bidding paradigm. We also provide a cryptographic security proof of our protocol on user profile.•Second, we propose an improved comparing scheme over encrypted data in our scenario, which is of high efficiency and security.•Third, we present a prototype to evaluate the efficiency of our protocol, and demonstrate that our prototype is efficient enough to be applied with a cautious choice of parameters.
Real-time bidding (RTB), one of the major trading mechanisms used for online advertising, allows the advertiser to make an impression-level bid decision. However, the security and privacy concerns of RTB are gaining increasing attention with the recent enforcement of the European Union General Data Protection Regulation (GDPR). In this study, we present a novel privacy-preserving RTB (Pri-RTB) protocol, which aims at preserving both data privacy and utility by performing additively homomorphic encryption on the user profile. To our knowledge, this is the first work to address the privacy issue of the RTB paradigm. We present a formal proof for the security of Pri-RTB under the assumption of the decisional Diffie–Hellman (DDH) problem. We analyze and elaborate the superiority of Pri-RTB over other related works. We also developed a prototype for Pri-RTB and conducted several experiments to evaluate its feasibility and efficiency under different parameters. Our experiments demonstrate that Pri-RTB can work highly efficiently in a practical setting (for example, a scenario with approximately 200 advertisers per auction).
Online behavioral advertising (OBA) is now the norm for social media advertising campaigns. Brands use detailed consumer data points to customize product placement, but extant research has found ...mixed results about the efficacy of OBA given increasing consumer privacy concerns. This research attempts to address this conflict by using the FCB grid to investigate how different product types (high vs. low involvement, thinking vs. feeling) might influence perceptions of privacy and subsequent ad attitudes. Using the Affect Infusion Model (AIM) and accessibility-diagnosticity framework, the authors demonstrate how low involvement 'feeling' products generate the highest ad attitudes. Participants in two studies respond more favorably to targeted ads for these products, and diagnosticity of affect-as-information is shown to be the mechanism for this effect. However, this effect only occurred when privacy concerns were low. Theoretical and practical implications are discussed.
Brands and social media platforms are two main players in online behavioral advertising (OBA), but the extant literature overlooks the interaction between them. Although advertising brands invest ...considerable resources to target potential consumers through social media advertising, our analysis indicates that publisher‐platform‐related activities can elicit negative consequences. Thus, we examined the role of perceived ad complicity, that is, consumers' perception regarding advertisers partnering with the social media platforms in the OBA process. We used perceived ad complicity as a moderator to explain the variation in consumers' negative responses to OBA in a social media context. Our results indicate that consumers with high perceived ad complicity experience greater perceived ad intrusiveness. This effect directly impacts their attitudes toward publisher platforms and advertising brands but consumers react more negatively toward brands (vs. publisher platforms) regarding this practice. Furthermore, we found that consumers who are more sensitive to social norms experience stronger perceived ad complicity and that informing consumers about why they are seeing specific ads on their social media platforms does not change their views on ad complicity.
PurposeThe research aims to investigate how individuals can be persuaded to make purchases through repeated and personalized messages. Specifically, the study proposes a framework of the potential ...benefits and risks of the online behavioral and data-driven digital advertising (OBA), which can help researchers and practitioners to better understand shopping behavior in the online retailing setting. In addition, the research focuses on the role of privacy concerns in affecting avoidance or adoption of OBA.Design/methodology/approachThe authors apply a structural equation modeling (SEM) approach with partial least square (PLS) regression method to test the research hypotheses through data coming from a structured questionnaire.FindingsOBA is a controversial type of advertising that activates opposing reactions on consumers' perspective. Specifically, acceptance of the OBA is positively related to relevance, usefulness and credibility of the personalized advertisements, while the intention to avoid personalized ads is strictly related to the privacy concerns. Consequently, OBA acceptance and avoidance affected the click intention on the ad and the behavioral intention that are decisive for the success of data-driven digital advertising.Originality/valuePrior research came up with complex theoretical frameworks that explain antecedents of OBA focusing only on ethical issues in marketing, on the effectiveness of a single OBA campaign or on how to create a successful advertising campaign. However, no study focuses on the intended or actual behavior of shoppers. Specifically, filling the gap in the existing literature, our research applies an SEM approach to identify both benefits and risks and the antecedents of the actual behavior of individuals in terms of actual purchases promoted by OBA.
Quality Assessment and Biases in Reused Data Fernández-Ardèvol, Mireia; Rosales, Andrea
The American behavioral scientist (Beverly Hills),
05/2024, Letnik:
68, Številka:
5
Journal Article
Recenzirano
This article investigates digital and non-digital traces reused beyond the context of creation. A central idea of this article is that no (reused) dataset is perfect. Therefore, data quality ...assessment becomes essential to determine if a given dataset is “good enough” to be used to fulfill the users’ goals. Biases, a possible source of discrimination, have become a relevant data challenge. Consequently, it is appropriate to analyze whether quality assessment indicators provide information on potential biases in the dataset. We use examples representing two opposing sides regarding data access to reflect on the relationship between quality and bias. First, the European Union open data portal fosters the democratization of data and expects users to manipulate the databases directly to perform their analyses. Second, online behavioral advertising systems offer individualized promotional services but do not share the datasets supporting their design. Quality assessment is socially constructed, as there is not a universal definition but a set of quality dimensions, which might change for each professional context. From the users’ perspective, trust/credibility stands out as a relevant quality dimension in the two analyzed cases. Results show that quality indicators (whatever they are) provide limited information on potential biases. We suggest that data literacy is most needed among both open data users and clients of behavioral advertising systems. Notably, users must (be able to) understand the limitations of datasets for an optimal and bias-free interpretation of results and decision-making.
This paper inspects the relationship between purchase intention in social media context and relevant factors namely: trust, perceived risk, online behavioral advertising, and social commerce ...constructs. Using judgmental sampling technique, 384 questionnaires across Lebanon were collected and analyzed using structural equation modeling (SEM). The results show that purchase intention of the respondents is significantly positively affected by social commerce constructs, trust, and online behavioral advertising. And trust is positively enriched by social commerce constructs. Also, it is clear that positive social commerce constructs will decrease the perception of risks between customers when shopping online. Perceived risk influence on purchase intention is not significant, Trust negatively impacts perceived risk. This paper shows specific inferences about the factors affecting buying intention in social commerce. It provides fruitful insights to both academic researchers and professional marketers. In terms of limitations, other factors might be added and be under examination; that might include value perceptions, social presence, social proof, and artificial intelligence agents such as Facebook chatbots. In addition, other product categories are useful to get more insights about the intentions of customers; such as cosmetics, home appliances, phones, and other service industries as cleaning, laundry, financial services, etc. The study attempted to examine potential factors to evaluate the purchase intentions (PI) in the social commerce context in Lebanon. It extends the earlier literature by providing clues about the positive influence of OBA on PI.
Due to the rapid proliferation in the algorithm-driven online tracking and profiling infrastructure, and the increasing business potential of online behavioral advertising, researchers from various ...disciplines are attracted to the growing body of knowledge on the phenomenon. Although the literature on online behavioral advertising is accumulating, the stream of research is still in the development stage, hence is highly fragmented. This paper aims to review, organize, and integrate the literature on online behavioral advertising and assess the-state-of-the-art in order to facilitate future research. The review covers 80 peer-reviewed journal articles from 47 scholarly journals published between 2000 and 2018. The resulting framework summarizes the progress in online behavioral advertising research and provides future research directions.
Online native advertising is increasingly targeted based on people's online behavior. This study examines the effects of online behaviorally targeted native advertising on ad and brand responses. In ...addition, it tests two competing explanatory mechanisms that are suggested in the literature on online behavioral advertising that may result in opposing persuasion outcomes: perceived personal relevance of the advertisement and understanding of online behavioral advertising as a persuasive tactic. An experiment showed that behaviorally targeted native advertising resulted in higher perceived personal relevance than native advertising, which consequently had a positive effect on persuasion (i.e., ad and brand responses). Although behaviorally targeted native advertising (versus native advertising) induced persuasion knowledge of online behavioral advertising as a persuasion tactic, this did not negatively affect persuasion. This study provides new insights into the theoretical mechanisms that explain behaviorally targeted native advertising effects and has implications for the advertising practice.
•Learning about an invisible digital identity can foster enhanced digital literacy.•Tracking technologies reveal information about users.•Object-oriented rhetoric helps theorize the relationship ...between computer algorithms and humans.
Using tracking cookies and web beacons, online behavioral advertising uses code stored on machines to access users’ Internet habits to customize advertisements and better market goods to consumers. This trend of tracking user movements has become concerning because the technologies used reveal personal information about the user to companies. Users can become more informed about the tracking technologies by visiting two websites that provide information about the trackers and give ways to opt-out of tracking technologies. This article provides a historical overview of tracking technologies, analyzes AboutAds.info and the online privacy tool Ghostery <ghostery.com>, theorizes what networked culture means in the 21st century, and closes with a heuristic for educators to use in their classrooms for discussions about invisible digital identity on the web.
PDF
