Vying voices of the pandemic

This article documents and explores the painful impact of a gruesome racial attack during the first lockdown in the wake of the Covid-19 pandemic. It occurred less than a fortnight before the brutal murder of George Floyd in America. It is a reflection on the issue of racism and the marginalisation of less dominant groups in and outside the borders of Great Britain. It is the recognition and exploration in myself of an internalised colony of voices emerging as a response to the traumatic event. Tracking the intra-psychic and interpersonal dynamics involved in the racism and the subsequent attempt at an anti-racist answer leads to self-reflection on my part and the confrontation of my own bias. Eventually, I can feel my underlying vulnerability and the resulting shift. The sense of self-awareness and agency evolves into the mobilisation of an extensive mentalizing process. The article attempts to capture the subtle, insidious nature of othering and the fear behind the defences we use to keep this in place; the centrality of our capacity to courageously embrace our vulnerability as crucial to our ability to embrace and treat with dignity people who are different from us. The article touches on hopefulness that one day this socially constructed monster, racism, would be a thing of the past, not just on paper but in the human psyche also.

From Behavioral Design to Reverence for Life: Care Policies for the Digital Environment

The article raises the problem of the ecology of a human being in a digital reality, namely, the issue of caring for a resource accessible to any person living in new conditions. The aim of the study is to substantiate the need for a transition from the behavioral design as well as the corresponding ethological paradigm to the existential design, involving a more responsible and careful approach to ecology and ethics in human capital management in the context of cognitive capitalism and digitalization of life. In the modern world it is often the question of productivity growth and technological advancement. Meanwhile, the question of human capacities and incapacities (mental, physical, behavioral) does not arise. Taking into account the absence of a caring attitude towards human capacities, this resource will never go turn into human capital. The research demonstrates that the design of digital media allows the use of the available human resources more properly if technical requirements of speed, quantity, simplicity are changed in compliance with existential requirements (changes in the subject of herself/himself, not in the objects of her/his activities) increasing his/her role, ethical meaning, feeling of presence in the event, tracking the results of actions and a deeper awareness of the results. The article is aimed at media philosophers, anthropologists and theorists of digital culture.

An Automatic Participant Detection Framework for Event Tracking on Twitter

Topic Detection and Tracking (TDT) on Twitter emulates human identifying developments in events from a stream of tweets, but while event participants are important for humans to understand what happens during events, machines have no knowledge of them. Our evaluation on football matches and basketball games shows that identifying event participants from tweets is a difficult problem exacerbated by Twitter’s noise and bias. As a result, traditional Named Entity Recognition (NER) approaches struggle to identify participants from the pre-event Twitter stream. To overcome these challenges, we describe Automatic Participant Detection (APD) to detect an event’s participants before the event starts and improve the machine understanding of events. We propose a six-step framework to identify participants and present our implementation, which combines information from Twitter’s pre-event stream and Wikipedia. In spite of the difficulties associated with Twitter and NER in the challenging context of events, our approach manages to restrict noise and consistently detects the majority of the participants. By empowering machines with some of the knowledge that humans have about events, APD lays the foundation not just for improved TDT systems, but also for a future where machines can model and mine events for themselves.

Gaze and Event Tracking for Evaluation of Recommendation-Driven Purchase

Recommendation systems play an important role in e-commerce turnover by presenting personalized recommendations. Due to the vast amount of marketing content online, users are less susceptible to these suggestions. In addition to the accuracy of a recommendation, its presentation, layout, and other visual aspects can improve its effectiveness. This study evaluates the visual aspects of recommender interfaces. Vertical and horizontal recommendation layouts are tested, along with different visual intensity levels of item presentation, and conclusions obtained with a number of popular machine learning methods are discussed. Results from the implicit feedback study of the effectiveness of recommending interfaces for four major e-commerce websites are presented. Two different methods of observing user behavior were used, i.e., eye-tracking and document object model (DOM) implicit event tracking in the browser, which allowed collecting a large amount of data related to user activity and physical parameters of recommending interfaces. Results have been analyzed in order to compare the reliability and applicability of both methods. Observations made with eye tracking and event tracking led to similar results regarding recommendation interface evaluation. In general, vertical interfaces showed higher effectiveness compared to horizontal ones, with the first and second positions working best, and the worse performance of horizontal interfaces probably being connected with banner blindness. Neural networks provided the best modeling results of the recommendation-driven purchase (RDP) phenomenon.

Regional Event-Marketing: Multi-Criteria Evaluation of the Effectiveness of the Events in Tambov

The article considers the problems of assessing the effectiveness of event marketing on the example of regional events held in the city of Tambov. The results of a survey of residents who participated in such events are presented. Criteria are presented that increase the satisfaction of citizens and, as a consequence, affect the recognition of both the event itself at the regional level and the commercial brands involved in organizing and conducting the event. Tracking of brands’ health has been created. Recommendations for improving the communication efficiency of event marketing are given.

Evaluation of a Sick Employee Online Log System for Tracking Sick Hospital Employees During Two Influenza Seasons

Background: Since 2009, Vidant Health has used a Sick Employee Online Log (SEOL) system to track illnesses among employees and to capture this information in real time. The CDC assessed the 2017–2018 influenza season as a high-severity influenza season, whereas the 2018–2019 influenza season was of moderate severity. Objective: In this research project, we sought to determine whether the influenza season severity would affect either the hospital-based employee illness surveillance system results or would correlate with state influenza-like illness (ILI) visits. Methods: The SEOL system is an internet-based system initiated in December 2008. When a hospital employee calls in sick, the department manager records whether the employee reports the following symptoms: nausea, vomiting, diarrhea, upper respiratory infection, fever, sore throat, headache, conjunctivitis, rash, and/or cough. The information is confidential, with raw data access restricted to review by occupational health and infection control leadership. The correlation value was determined for each symptom using the North Carolina Division of Human Services (NC DHHS) percentage of ILI visits in statewide emergency departments.1 The data collection dates covered January 1–May 31 for each year. In this study, only symptoms related to influenza were included: upper respiratory infection, fever, influenza-like illness, cough and self-reported influenza. Correlation values were calculated using MS Excel software. Results: There were no breaks in confidentiality. All of the correlation values had a correlation value of 0.5 or better (Fig. 1), showing good correlation with the NC DHHS ILI data for both years; however, the more severe 2017–2018 influenza season had correlation values of 0.7 for all symptoms, versus 0.52–0.59 for URI and ILI, respectively, only during 2018–2019. Conclusions: The higher-severity influenza season did correlate with a higher r values when compared to North Carolina’s DHHS ILI emergency department data than did the influenza season of moderate severity. A possible explanation is that a higher-severity influenza season would correlate better than a moderate influenza season because it shows fewer ILI peaks and troughs. In conclusion, the SEOL system served as an early warning that influenza is present among our staff, and it correlates well with the state system for ILI surveillance. Potential limitations of SEOL are that respiratory symptoms are not specific to influenza; thus, they are subject to variation due to other respiratory viruses circulating among our employees.1. The North Carolina Disease Event Tracking and Epidemiologic Collection Tool. NC DETECT website. http://www.ncdetect.org. Accessed Nov 8, 2019.Funding: NoneDisclosures: None