Perception of COVID-19 vaccination among Indian Twitter users: computational approach.

Unlabelled: Vaccination has been a hot topic in the present COVID-19 context. The government, public health stakeholders and media are all concerned about how to get the people vaccinated. The study was intended to explore the perception and emotions of the Indians citizens toward COVID-19 vaccine from Twitter messages.

Development of database structure and indexing for siddha medicine system - A platform for siddha literature analytics.

Background: Siddha Medicine system is one among the oldest traditional systems of medicines in India and has its entire literature in the Tamil language in the form of poems ( in tamil). Even if the siddha poems are available in public domain, they are not known to other parts of the world because, researchers of other languages are not able to understand the contents of these poems and there exists a language barrier. Hence there is a need to develop a system to extract structured information from these texts to facilitate searching, comparing, analysis and implementing.

Social media analytics and reachability evaluation - #Diabetes.

Background And Aims: Diabetes as a lifestyle disorder could be effectively managed by creating awareness among people through social media. Understanding the content of Twitter messages will aid in strategizing health communication about diabetes to the community through Twitter. This study aimed to analyze the content, sentiment, and reachability of diabetes related tweets posted in India.

Use of social media data for disease based social network analysis and network modeling: A Systematic Review.

Burden due to infectious and noncommunicable disease is increasing at an alarming rate. Social media usage is growing rapidly and has become the new norm of communication. It is imperative to examine what is being discussed in the social media about diseases or conditions and the characteristics of the network of people involved in discussion.

What people share about the COVID-19 outbreak on Twitter? An exploratory analysis.

Background: The recent outbreak of respiratory illness caused by COVID-19 in Wuhan, China, has received global attention as it has infected thousands of individuals there, and later it has also been reported from other countries internationally. This study aims at performing an exploratory study on Twitter to understand the information shared among the community regarding the COVID-19 outbreak.

Methods: COVID-19 related tweets were collected from Twitter using keywords from 18 January to 25 January 2020.

Spatio-temporal distribution of negative emotions on Twitter during floods in Chennai, India, in 2015: a post hoc analysis.

Background: Natural disasters are known to take their psychological toll immediately, and over the long term, on those living through them. Messages posted on Twitter provide an insight into the state of mind of citizens affected by such disasters and provide useful data on the emotional impact on groups of people. In 2015, Chennai, the capital city of Tamil Nadu state in southern India, experienced unprecedented flooding, which subsequently triggered economic losses and had considerable psychological impact on citizens.

A Systematic Review of Techniques Employed for Determining Mental Health Using Social Media in Psychological Surveillance During Disasters.

During disasters, people share their thoughts and emotions on social media and also provide information about the event. Mining the social media messages and updates can be helpful in understanding the emotional state of people during such unforeseen events as they are real-time data. The objective of this review is to explore the feasibility of using social media data for mental health surveillance as well as the techniques used for determining mental health using social media data during disasters.