The Web is a constantly evolving, complex system, with important implications for both marketers and consumers. In this paper, we contend that over the next five to ten years society will see a shift in the nature of the Web, as consumers, firms and regulators become increasingly concerned about privacy. In particular, we predict that, as a result of this privacy-focus, various information sharing and protection practices currently found on the Dark Web will be increasingly adapted in the overall Web, and in the process, firms will lose much of their ability to fuel a modern marketing machinery that relies on abundant, rich, and timely consumer data. In this type of controlled information-sharing environment, we foresee the emersion of two distinct types of consumers: (1) those generally willing to share their information with marketers (Buffs), and (2) those who generally deny access to their personal information (Ghosts). We argue that one way marketers can navigate this new environment is by effectively designing and deploying conversational agents (CAs), often referred to as "chatbots." In particular, we propose that CAs may be used to understand and engage both types of consumers, while providing personalization, and serving both as a form of differentiation and as an important strategic asset for the firm-one capable of eliciting self-disclosure of otherwise private consumer information.

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A procedure for reflection and discourse on the behavior of bots in the context of law, deception, and societal norms.

The highly pathogenic avian influenza virus (HPAIV) H5N1 A/goose/Guangdong/1996 lineage (Gs/GD) is endemic in poultry across several countries in the world, and has caused lethal, sporadic infections in humans. Vaccines are important in HPAI control for both poultry and in pre-pandemic preparedness in humans. This study assessed inactivated pre-pandemic vaccine strains in a One Health framework, focusing on the genetic and antigenic diversity of field H5N1 Gs/GD viruses from the agricultural sector and assessing cross protection in a chicken challenge model. Nearly half (47.92%) of the forty-eight combinations of vaccine/challenge viruses examined had bird protection of 80% or above. Most vaccinated groups had prolonged mean death time (MDT) and the virus shedding titers were significantly lower compared to the sham group (p≤ 0.05). The antibody titers in the pre-challenge sera were not predictive of protection. Although vaccinated birds had higher titers of hemagglutination inhibiting (HI) antibodies against homologous vaccine antigen, most of them also had lower or no antibody titer against the challenge antigen. The comparison of all parameters, homologous or closely related vaccine and challenge viruses, gave the best prediction protection. Through additional analysis, we identified a pattern of epitopes substitutions in the hemagglutinin (HA) of each challenge virus that impacted protection, regardless of the vaccine used. These changes were situated in the antigenic sites and/or reported epitopes associated with virus escape from antibody neutralization. As a result, this study highlights virus diversity, immune response complexity, and the importance of strain selection for vaccine development to control H5N1 HPAIV in the agricultural sector and for human pre-pandemic preparedness. We suggest that the engineering of specific antigenic sites can improve the immunogenicity of H5 vaccines. Importance The sustained circulation of highly pathogenic avian influenza virus (HPAIV) H5N1 A/goose/Guangdong/1996 lineage (Gs/GD) in the agricultural sector and some wild birds has led to the evolution and selection of distinct viral lineages involved in the escape from vaccine protection. Our results using inactivated vaccine candidates from the human pandemic preparedness program in a chicken challenge model identified critical antigenic conformational epitopes on the H5 hemagglutinin (HA) from different clades that were associated with antibody recognition and escape. Even though other investigators have reported epitope mapping in the H5 HA, much of this information pertains to epitopes reactive towards mouse antibodies. Our findings validate changes in antigenic epitopes of HA associated with virus escape from antibody neutralization in chickens, which has direct relevance to field protection and virus evolution. Therefore, the knowledge of these immunodominant regions is essential to proactively develop diagnostic tests, improve surveillance platforms to monitor AIV outbreaks, and design more efficient and broad-spectrum agricultural and human prepandemic vaccines.

Despite increased empirical attention, theory on bots and how they act to disseminate information on social media remains poorly understood. Our study leverages the conduit brokerage perspective and the findings of a multiple case study to develop a novel framework of algorithmic conduit brokerage for understanding information dissemination by bots and the design choices that may influence their actions. Algorithmic conduit brokerage encompasses two intertwined processes. The first process, algorithmic social alertness, relies on bot activity to curate and reconfigure information. Algorithmic social alertness is significant because it involves action triggers that dictate the kinds of information being searched, discovered, and retrieved by bots. The second process, algorithmic social transmission, relies on bot activity to embellish and distribute the information curated. Algorithmic social transmission is important because it can broaden the reach of information disseminated by bots through increased discoverability and directed targeting. The two algorithmic conduit brokerage processes we offer are unique to bots and distinct from the original conceptualization of conduit brokerage, which is rooted in human activity. First, since bots lack the human ability of sensemaking and are instead fueled by automation and action triggers rather than by emotions, algorithmic conduit brokerage is more invariant and reliable than human conduit brokerage. Second, automation increases the speed and scale of information curation and transfer, making algorithmic conduit brokerage not only more consistent but also faster and more extensive. Third, algorithmic conduit brokerage includes a set of new concepts (e.g., action triggers and rapid scaling) that are specific to bots and therefore not applicable to human conduit brokerage.