Understanding the intent behind sharing misinformation on social media

Several studies have been conducted in annotating and collecting the misinformation spread on various social media sites. The misinformation spread during COVID-19 pandemic increased many folds. Understanding the reasons and intent of the misinformation during COVID-19 is a crucial task. Existing approaches have not focused on understanding the intent behind sharing misinformation in the first place. To understand the intent, we introduce a new dataset MisMemoir that apart from annotating misinformation, also collects the social context and site history of the user sharing misinformation. Utilising the established benefits of game theory in social media behaviour analysis, we deploy two-person cooperative games to understand how prominent positive feedback cues like likes and retweets are in motivating an individual to share misinformation on the platform Twitter. Experimental results demonstrate that the spread of misinformation's primary intent is the intentional/unintentional manoeuvre to increased reach and possibly a false sense of accomplishment. Empirically, we show that in a competitive environment like social media, feedback cues like retweets and comments assume the role of 'attention' payoff that significantly affects the strategy of a user on Twitter to share misinformation intentionally. [ FROM AUTHOR] Copyright of Journal of Experimental & Theoretical Artificial Intelligence is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Understanding the intent behind sharing misinformation on social media

Several studies have been conducted in annotating and collecting the misinformation spread on various social media sites. The misinformation spread during COVID-19 pandemic increased many folds. Understanding the reasons and intent of the misinformation during COVID-19 is a crucial task. Existing approaches have not focused on understanding the intent behind sharing misinformation in the first place. To understand the intent, we introduce a new dataset MisMemoir that apart from annotating misinformation, also collects the social context and site history of the user sharing misinformation. Utilising the established benefits of game theory in social media behaviour analysis, we deploy two-person cooperative games to understand how prominent positive feedback cues like likes and retweets are in motivating an individual to share misinformation on the platform Twitter. Experimental results demonstrate that the spread of misinformation’s primary intent is the intentional/unintentional manoeuvre to increased reach and possibly a false sense of accomplishment. Empirically, we show that in a competitive environment like social media, feedback cues like retweets and comments assume the role of ‘attention’ payoff that significantly affects the strategy of a user on Twitter to share misinformation intentionally.

A non-invasive ultrasensitive diagnostic approach for COVID-19 infection using salivary label-free SERS fingerprinting and artificial intelligence.

Clinical diagnostics for SARS-CoV-2 infection usually comprises the sampling of throat or nasopharyngeal swabs that are invasive and create patient discomfort. Hence, saliva is attempted as a sample of choice for the management of COVID-19 outbreaks that cripples the global healthcare system. Although limited by the risk of eliciting false-negative and positive results, tedious test procedures, requirement of specialized laboratories, and expensive reagents, nucleic acid-based tests remain the gold standard for COVID-19 diagnostics. However, genetic diversity of the virus due to rapid mutations limits the efficiency of nucleic acid-based tests. Herein, we have demonstrated the simplest screening modality based on label-free surface enhanced Raman scattering (LF-SERS) for scrutinizing the SARS-CoV-2-mediated molecular-level changes of the saliva samples among healthy, COVID-19 infected and COVID-19 recovered subjects. Moreover, our LF-SERS technique enabled to differentiate the three classes of corona virus spike protein derived from SARS-CoV-2, SARS-CoV and MERS-CoV. Raman spectral data was further decoded, segregated and effectively managed with the aid of machine learning algorithms. The classification models built upon biochemical signature-based discrimination method of the COVID-19 condition from the patient saliva ensured high accuracy, specificity, and sensitivity. The trained support vector machine (SVM) classifier achieved a prediction accuracy of 95% and F1-score of 94.73%, and 95.28% for healthy and COVID-19 infected patients respectively. The current approach not only differentiate SARS-CoV-2 infection with healthy controls but also predicted a distinct fingerprint for different stages of patient recovery. Employing portable hand-held Raman spectrophotometer as the instrument and saliva as the sample of choice will guarantee a rapid and non-invasive diagnostic strategy to warrant or assure patient comfort and large-scale population screening for SARS-CoV-2 infection and monitoring the recovery process.

Evolving consensus on managing vitreo-retina and uvea practice in post-COVID-19 pandemic era

The COVID-19 pandemic has brought new challenges to the health care community. Many of the super-speciality practices are planning to re-open after the lockdown is lifted. However there is lot of apprehension in everyone's mind about conforming practices that would safeguard the patients, ophthalmologists, healthcare workers as well as taking adequate care of the equipment to minimize the damage. The aim of this article is to develop preferred practice patterns, by developing a consensus amongst the lead experts, that would help the institutes as well as individual vitreo-retina and uveitis experts to restart their practices with confidence. As the situation remains volatile, we would like to mention that these suggestions are evolving and likely to change as our understanding and experience gets better. Further, the suggestions are for routine patients as COVID-19 positive patients may be managed in designated hospitals as per local protocols. Also these suggestions have to be implemented keeping in compliance with local rules and regulations.

Insights from a Pan India Sero-Epidemiological survey (Phenome-India Cohort) for SARS-CoV2.

To understand the spread of SARS-CoV2, in August and September 2020, the Council of Scientific and Industrial Research (India) conducted a serosurvey across its constituent laboratories and centers across India. Of 10,427 volunteers, 1058 (10.14%) tested positive for SARS-CoV2 anti-nucleocapsid (anti-NC) antibodies, 95% of which had surrogate neutralization activity. Three-fourth of these recalled no symptoms. Repeat serology tests at 3 (n = 607) and 6 (n = 175) months showed stable anti-NC antibodies but declining neutralization activity. Local seropositivity was higher in densely populated cities and was inversely correlated with a 30-day change in regional test positivity rates (TPRs). Regional seropositivity above 10% was associated with declining TPR. Personal factors associated with higher odds of seropositivity were high-exposure work (odds ratio, 95% confidence interval, p value: 2.23, 1.92-2.59, <0.0001), use of public transport (1.79, 1.43-2.24, <0.0001), not smoking (1.52, 1.16-1.99, 0.0257), non-vegetarian diet (1.67, 1.41-1.99, <0.0001), and B blood group (1.36, 1.15-1.61, 0.001).