7 research outputs found
A Twitter narrative of the COVID-19 pandemic in Australia
Social media platforms contain abundant data that can provide comprehensive
knowledge of historical and real-time events. During crisis events, the use of
social media peaks, as people discuss what they have seen, heard, or felt.
Previous studies confirm the usefulness of such socially generated discussions
for the public, first responders, and decision-makers to gain a better
understanding of events as they unfold at the ground level. This study performs
an extensive analysis of COVID-19-related Twitter discussions generated in
Australia between January 2020, and October 2022. We explore the Australian
Twitterverse by employing state-of-the-art approaches from both supervised and
unsupervised domains to perform network analysis, topic modeling, sentiment
analysis, and causality analysis. As the presented results provide a
comprehensive understanding of the Australian Twitterverse during the COVID-19
pandemic, this study aims to explore the discussion dynamics to aid the
development of future automated information systems for epidemic/pandemic
management.Comment: Accepted to ISCRAM 202
From Pro, Anti to Informative and Hesitant: An Infoveillance study of COVID-19 vaccines and vaccination discourse on Twitter
COVID-19 pandemic has brought unprecedented challenges to the world, and
vaccination has been a key strategy to combat the disease. Since Twitter is one
of the most widely used public microblogging platforms, researchers have
analysed COVID-19 vaccines and vaccination Twitter discourse to explore the
conversational dynamics around the topic. While contributing to the crisis
informatics literature, we curate a large-scale geotagged Twitter dataset,
GeoCovaxTweets Extended, and explore the discourse through multiple
spatiotemporal analyses. This dataset covers a longer time span of 38 months,
from the announcement of the first vaccine to the availability of booster
doses. Results show that 43.4% of the collected tweets, although containing
phrases and keywords related to vaccines and vaccinations, were unrelated to
the COVID-19 context. In total, 23.1% of the discussions on vaccines and
vaccinations were classified as Pro, 16% as Hesitant, 11.4% as Anti, and 6.1%
as Informative. The trend shifted towards Pro and Informative tweets globally
as vaccination programs progressed, indicating a change in the public's
perception of COVID-19 vaccines and vaccination. Furthermore, we explored the
discourse based on account attributes, i.e., followers counts and tweet counts.
Results show a significant pattern of discourse differences. Our findings
highlight the potential of harnessing a large-scale geotagged Twitter dataset
to understand global public health communication and to inform targeted
interventions aimed at addressing vaccine hesitancy
STUDY OF IN VITRO ANTI-OXIDANT AND ANTI-DIABETIC ACTIVITY BY MUSSAENDA MACROPHYLLA ROOT EXTRACTS
Objective: The systematic study of effective alternative anti-diabetic drugs has great importance to manage diabetes as well as other oxidative stress-related diseases. According to previous research, root and bark of Mussaenda macrophylla plant has anti-microbial, anti-coagulant, anti-inflammatory, and hepatoprotective activity. Ethnomedicinal data shows that Mussaenda macrophylla is used to treat diabetes as well as oxidative stress. The objective of this research is to investigate in vitro anti-diabetic and anti-oxidant activity of root extract of Mussaenda macrophylla.
Methods: DPPH free radical scavenging assay was used to detect anti-oxidant potency of ethanol and methanol root extract of the plant and expressed as % of radicle inhibition. Anti-diabetic activity was determined by the glucose diffusion method using a glucose oxidase kit and results were expressed as mean±SD.
Results: The ethanol root extract at the concentration of 50 mg/ml and 100 mg/ml showed better glucose diffusion inhibition than that of methanol extract at the same concentration on increasing time interval. Ethanol extract at the concentration 100 µg/ml displayed better DPPH scavenging activity (89.83±0.19 %) than that of methanol extract (86.61±0.75%).
Conclusion: This study concluded that ethanol and methanol root extract of Mussenda macrophylla have potent anti-diabetic as well as anti-oxidant activity but further advance research is necessary in the animal model
Unzipping flood vulnerability and functionality loss:tale of struggle for existence of riparian buildings
Floods pose significant risk to riparian buildings as evidenced during many historical events. Although structural resilience to tsunami flooding is well studied in the literature, high-velocity and debris-laden floods in steep terrains are not considered adequately so far. Historical floods in steep terrains necessitate the need for flood vulnerability analysis of buildings. To this end, we report vulnerability of riparian-reinforced concrete buildings using forensic damage interpretations and empirical/analytical vulnerability analyses. Furthermore, we propose the concept and implications of functionality loss due to flooding in residential reinforced concrete (RC) buildings using empirical data. Fragility functions using inundation depth and momentum flux are presented for RC buildings considering a recent flooding event in Nepal. The results show that flow velocity and sediment load, rather than hydrostatic load, govern the damages in riparian RC buildings. However, at larger inundation depth, hydrostatic force alone may collapse some of the RC buildings
BillionCOV: An enriched billion-scale collection of COVID-19 tweets for efficient hydration
The COVID-19 pandemic has introduced new norms, such as social distancing, face masks, quarantine, lockdowns, travel restrictions, work/study from home, and business closures, to name a few. The pandemic’s seriousness has made people vocal on social media, especially on microblogs such as Twitter. Since the early days of the outbreak, researchers have been collecting and sharing large-scale datasets of COVID-19 tweets. However, the existing datasets carry issues related to proportion and redundancy. We report that more than 500 million tweet identifiers point to deleted or protected tweets. To address these issues, this paper introduces an enriched global billion-scale English-language COVID-19 tweets dataset, BillionCOV,1 which contains 1.4 billion tweets originating from 240 countries and territories between October 2019 and April 2022. Importantly, BillionCOV facilitates researchers to filter tweet identifiers for efficient hydration. We anticipate that the dataset of this scale with global scope and extended temporal coverage will aid in obtaining a thorough understanding of the pandemic’s conversational dynamics