PANOLA: A Personal Assistant for Supporting Users in Preserving Privacy

Privacy is the right of individuals to keep personal information to themselves. When individuals use online systems, they should be given the right to decide what information they would like to share and what to keep private. When a piece of information pertains only to a single individual, preserving privacy is possible by providing the right access options to the user. However, when a piece of information pertains to multiple individuals, such as a picture of a group of friends or a collaboratively edited document, deciding how to share this information and with whom is challenging. The problem becomes more difficult when the individuals who are affected by the information have different, possibly conflicting privacy constraints. Resolving this problem requires a mechanism that takes into account the relevant individuals’ concerns to decide on the privacy configuration of information. Because these decisions need to be made frequently (i.e., per each piece of shared content), the mechanism should be automated. This article presents a personal assistant to help end-users with managing the privacy of their content. When some content that belongs to multiple users is about to be shared, the personal assistants of the users employ an auction-based privacy mechanism to regulate the privacy of the content. To do so, each personal assistant learns the preferences of its user over time and produces bids accordingly. Our proposed personal assistant is capable of assisting users with different personas and thus ensures that people benefit from it as they need it. Our evaluations over multiagent simulations with online social network content show that our proposed personal assistant enables privacy-respecting content sharing.

An Analysis of Social Network Activities of College Students

The present exploratory study was taken up to know about the various social networking sites that students use and the type of information shared by them on them. WhatsApp emerged as the most preferred medium for sharing messages, photos, and videos. There was a significant difference between the use of social media networks and the content shared on them. Content related to music, cooking, and movies were watched on the top three social networking sites namely YouTube, WhatsApp, and Instagram. The study found a significant difference between watched social media networks. There exists a significant difference regarding the different contents watched on social media. A significant difference between watched and shared content in different social media networks was also established. The three most important advantages of social media as perceived by the students were convenience in keeping in touch with friends, ease to learn new technology, knowledge of various academic institutions for higher studies across the country. Three disadvantages indicated by the study group were less physical activity, cybercrime, and privacy issues.

Sentiment analysis of tweets on prior authorization.

322 Background: Natural language processing (NLP) algorithms can be leveraged to better understand prevailing themes in healthcare conversations. Sentiment analysis, an NLP technique to analyze and interpret sentiments from text, has been validated on Twitter in tracking natural disasters and disease outbreaks. To establish its role in healthcare discourse, we sought to explore the feasibility and accuracy of sentiment analysis on Twitter posts (‘’tweets’’) related to prior authorizations (PAs), a common occurrence in oncology built to curb payer-concerns about costs of cancer care, but which can obstruct timely and appropriate care and increase administrative burden and clinician frustration. Methods: We identified tweets related to PAs between 03/09/2021-04/29/2021 using pre-specified keywords [e.g., #priorauth etc.] and used Twarc, a command-line tool and Python library for archiving Twitter JavaScript Object Notation data. We performed sentiment analysis using two NLP models: (1) TextBlob (trained on movie reviews); and (2) VADER (trained on social media). These models provide results as polarity, a score between 0-1, and a sentiment as ‘’positive’’ (>0), ‘’neutral’’ (exactly 0), or ‘’negative’’ (<0). We (AG, NP) manually reviewed all tweets to give the ground truth (human interpretation of reality) including a notation for sarcasm since models are not trained to detect sarcasm. We calculated the precision (positive predictive value), recall (sensitivity), and the F1-Score (measure of accuracy, range 0-1, 0=failure, 1=perfect) for the models vs. the ground truth. Results: After preprocessing, 964 tweets (mean 137/ week) met our inclusion criteria for sentiment analysis. The two existing NLP models labeled 42.4%- 43.3% tweets as positive, as compared to the ground truth (5.6% tweets positive). F-1 scores of models across labels ranged from 0.18-0.54. We noted sarcasm in 2.8% of tweets. Detailed results in Table. Conclusions: We demonstrate the feasibility of performing sentiment analysis on a topic of high interest within clinical oncology and the deficiency of existing NLP models to capture sentiment within oncologic Twitter discourse. Ongoing iterations of this work further train these models through better identification of the tweeter (patient vs. health care worker) and other analytics from shared content.[Table: see text]

Social media as author-audience games

We present an approach for the prediction of user authorship and feedback behavior with shared content. We consider that users use models of other users and their feedback to choose what to publish next. We look at the problem as a game between authors and audiences and relate it to current content-based user modeling solutions with no prior strategic models. As applications, we consider the large-scale authorship of Wikipedia pages, movies and food recipes. We demonstrate analytic properties, authorship and feedback prediction results, and an overall framework to study content authorship regularities in social media.

Assessing the Social Media User’s Credibility Rating of Shared Content, and its Utilization in Decision Making

This study seeks to ascertain the degree to which people rely on unprofessionally processed information from social media to make decisions or take critical actions. Professional media, in this case, refers to the traditional broadcast and print media who have been in the business of professionally processing and authenticating information for their audiences. While social media represent the various platforms for social exchange of information. Relevant to this study is the social media’s ability to reach multitudes of people with unsubstantiated information. The methodology employed is simple random sampling, using questionnaire as an instrument. 350 respondents provided input using three age ranges, 20-35, 36-50, and 50 and above. The results show social media usage as the only news source for the youngest age group at 38%. The 50 plus years mainly rely on professional media. While all three age groups admitted to sharing of unsubstantiated information at 68%, only 30% admit to using critical information from social media. Most importantly, the findings indicate; where prevalence and availability tends to overwhelm users, taking the time to seek more credible information takes a back seat, even in cases where the information sought is critical to decision making and use. Doi: 10.28991/esj-2021-01269 Full Text: PDF

Down to a r/science: Integrating Computational Approaches to the Study of Credibility on Reddit

Digital trace data enable researchers to study communication processes at a scale previously impossible. We combine social network analysis and automated content analysis to examine source and message factors’ impact on ratings of user-shared content. We found that the expertise of the author, the network position that the author occupies, and characteristics of the content the author creates have a significant impact on how others respond to that content. By observationally examining a large-scale online community, we provide a real-world test of how message consumers react to source and message characteristics. Our results show that it is important to think of online communication as occurring interactively between networks of individuals, and that the network positions people inhabit may inform their behavior.

In search for shared content and design in supervision training: a syllabus analysis in Sweden

PurposePrevious research has pointed to a lack of studies concerning supervision training courses. Consequently, the literature has little to suggest, and the research field is underexplored, so questions around the content and design of supervision training courses remain unanswered and need to be addressed systematically. The main aim of the present study is to explore and map whether shared content and design exist in supervisor training courses across different vocations.Design/methodology/approachA syllabus analysis is used in order to investigate characteristic features in supervisor training courses related to the professions of dentist, doctor, psychologist, police officer and teacher.FindingsThe results point to the existence of shared content in the different courses, such as an emphasis on learning and supervision theories, feedback, ethics, assessment and communication. Furthermore, the results conclude similarities in design of the courses, such as a problem-based approach, seminars, lectures and homework. Thus, there are common theoretical approaches to important supervisory competences.Practical implicationsOur results intend to offer possibilities to learn from different professions when improving supervisor training courses but may also constitute a starting point for developing a shared model of interprofessional supervisor competences. Furthermore, the results may support possible cooperation in interprofessional courses. This could include arranging interprofessional courses, where one part is shared for participants from the included professions and another part is profession-specific.Originality/valueWe seek to contribute to the research field of supervision at workplaces with knowledge and ideas about how to learn from different professions when developing and improving supervisor training courses.

Social Media as a Communication Channel

In digital world, people spend most of their time on social media. Social media has gone beyond being just an online communication platform. It has become a channel that users prefer to other online platforms, such as websites, blogs, forums to get information about various businesses, events, and individuals. With Industry 4.0, all devices are connected to online platform, smart devices get more place in daily life. Instead of accessing information through individual applications, consumers prefer to obtain information from the company's social media pages and/or the company's internal and external customers' shared content. The purpose of the chapter is to indicate the importance of social media use, for organizations to interact effectively with all stakeholders, and to explain the benefits of social media usage of organizations in terms of different functions with examples from best cases and results of empirical researches.

Meer van hetzelfde? Content sharing bij Vlaamse DPG Media-kranten

Content sharing at DPG Media’s Flemish newspaper brands Belgium’s Dutch-speaking region Flanders has seen a wave of mergers & acquisitions (M&As) in recent years, leading to, according to the government-owned media watchdog, a highly concentrated Flemish media market (). The latest newly founded company is DPG Media, in which the majority of all commercially owned major Flemish news outlets has seen its newsrooms merged into the same Antwerp-based building in early 2020. In this paper, we assess content homogeneity between the print and online versions of the two main newspapers of DPG Media by coding and analysing a sample of articles from 2018, 2019 and 2020. Results reveal only limited increases in shared content for the time being. Through distinguishing betweeninternaland external media concentration, the study serves as a steppingstone towards further content analysis research, in Flanders and beyond.