Fine-tuned Sentiment Analysis of COVID-19 Vaccine-Related Social Media Data: Comparative Study

This study investigated and compared public sentiment related to COVID-19 vaccines expressed on two popular social media platforms, Reddit and Twitter, harvested from January 1, 2020, to March 1, 2022. To accomplish this task, we created a fine-tuned DistilRoBERTa model to predict sentiments of approximately 9.5 million Tweets and 70 thousand Reddit comments. To fine-tune our model, our team manually labeled the sentiment of 3600 Tweets and then augmented our dataset by the method of back-translation. Text sentiment for each social media platform was then classified with our fine-tuned model using Python and the Huggingface sentiment analysis pipeline. Our results determined that the average sentiment expressed on Twitter was more negative (52% positive) than positive and the sentiment expressed on Reddit was more positive than negative (53% positive). Though average sentiment was found to vary between these social media platforms, both displayed similar behavior related to sentiment shared at key vaccine-related developments during the pandemic. Considering this similar trend in shared sentiment demonstrated across social media platforms, Twitter and Reddit continue to be valuable data sources that public health officials can utilize to strengthen vaccine confidence and combat misinformation. As the spread of misinformation poses a range of psychological and psychosocial risks (anxiety, fear, etc.), there is an urgency in understanding the public perspective and attitude toward shared falsities. Comprehensive educational delivery systems tailored to the population's expressed sentiments that facilitate digital literacy, health information-seeking behavior, and precision health promotion could aid in clarifying such misinformation.Comment: 11 Pages, 5 Figures, and 1 Tabl

Exploring celebrity influence on public attitude towards the COVID-19 pandemic: social media shared sentiment analysis

The COVID-19 pandemic has introduced new opportunities for health communication, including an increase in the public use of online outlets for health-related emotions. People have turned to social media networks to share sentiments related to the impacts of the COVID-19 pandemic. In this paper we examine the role of social messaging shared by Persons in the Public Eye (i.e. athletes, politicians, news personnel) in determining overall public discourse direction. We harvested approximately 13 million tweets ranging from 1 January 2020 to 1 March 2022. The sentiment was calculated for each tweet using a fine-tuned DistilRoBERTa model, which was used to compare COVID-19 vaccine-related Twitter posts (tweets) that co-occurred with mentions of People in the Public Eye. Our findings suggest the presence of consistent patterns of emotional content co-occurring with messaging shared by Persons in the Public Eye for the first two years of the COVID-19 pandemic influenced public opinion and largely stimulated online public discourse. We demonstrate that as the pandemic progressed, public sentiment shared on social networks was shaped by risk perceptions, political ideologies and health-protective behaviours shared by Persons in the Public Eye, often in a negative light.Comment: 7 Pages, 4 Figure

A Small Peptide Increases Drug Delivery in Human Melanoma Cells

Melanoma is the most fatal type of skin cancer and is notoriously resistant to chemotherapies. The response of melanoma to current treatments is difficult to predict. To combat these challenges, in this study, we utilize a small peptide to increase drug delivery to melanoma cells. A peptide library array was designed and screened using a peptide array-whole cell binding assay, which identified KK-11 as a novel human melanoma-targeting peptide. The peptide and its D-amino acid substituted analogue (VPWxEPAYQrFL or D-aa KK-11) were synthesized via a solid-phase strategy. Further studies using FITC-labeled KK-11 demonstrated dose-dependent uptake in human melanoma cells. D-aa KK-11 significantly increased the stability of the peptide, with 45.3% remaining detectable after 24 h with human serum incubation. Co-treatment of KK-11 with doxorubicin was found to significantly enhance the cytotoxicity of doxorubicin compared to doxorubicin alone, or sequential KK-11 and doxorubicin treatment. In vivo and ex vivo imaging revealed that D-aa KK-11 distributed to xenografted A375 melanoma tumors as early as 5 min and persisted up to 24 h post tail vein injection. When co-administered, D-aa KK-11 significantly enhanced the anti-tumor activity of a novel nNOS inhibitor (MAC-3-190) in an A375 human melanoma xenograft mouse model compared to MAC-3-190 treatment alone. No apparent systemic toxicities were observed. Taken together, these results suggest that KK-11 may be a promising human melanoma-targeted delivery vector for anti-melanoma cargo

Reports on the 2015 AAAI Workshop Program

Knowledge, Skill, and Behavior Transfer in Autonomous Robots: report on p. 9

Examining the Implementation of Digital Health to Strengthen the COVID-19 Pandemic Response and Recovery and Scale up Equitable Vaccine Access in African Countries

The COVID-19 pandemic has profoundly impacted the world, having taken the lives of over 6 million individuals. Accordingly, this pandemic has caused a shift in conversations surrounding the burden of diseases worldwide, welcoming insights from multidisciplinary fields including digital health and artificial intelligence. Africa faces a heavy disease burden that exacerbates the current COVID-19 pandemic and limits the scope of public health preparedness, response, containment, and case management. Herein, we examined the potential impact of transformative digital health technologies in mitigating the global health crisis with reference to African countries. Furthermore, we proposed recommendations for scaling up digital health technologies and artificial intelligence-based platforms to tackle the transmission of the SARS-CoV-2 and enable equitable vaccine access. Challenges related to the pandemic are numerous. Rapid response and management strategies - that is, contract tracing, case surveillance, diagnostic testing intensity, and most recently vaccine distribution mapping - can overwhelm the health care delivery system that is fragile. Although challenges are vast, digital health technologies can play an essential role in achieving sustainable resilient recovery and building back better. It is plausible that African nations are better equipped to rapidly identify, diagnose, and manage infected individuals for COVID-19, other diseases, future outbreaks, and pandemics.Comment: 8 Pages, 0 Figur

When Mommy Blogs are Semantically Tagged

Abstract. OWL 2-supported Semantic Tagging is a non compulsory yet decisive and highly influential component of a multidisciplinary knowledge architecture framework which synergetically combines the Semantic and the Social Webs. The facility consists of a semantic tagging layer based on OWL 2 axioms and expressions enticing social network users, typically mommy bloggers, to annotate their chaos of textual data with natural language verbalized versions of ontological elements. This paper provides a comprehensive short summary of the overall framework along with its backbone metamodel and its parenting analysis and surveillance ontology ParOnt, laying a particular emphasis on its semantic expression-based tagging feature, and accordingly highlighting the attained gains and improvements in terms of effective results, services and recommendations, all falling in the scope of public parenting orientation and awareness