Exploring stroke discourse on Twitter through content and network analysis among Indian users.

The study aimed to understand stroke-related Twitter conversations in India, focusing on topics, message sources, reach, and influential users to provide insights to stakeholders regarding community needs for knowledge, support, and interventions. Geo-tagged Twitter posts focusing on stroke originating from India and, spanning from November 7, 2022, to February 28, 2023, were systematically obtained via the Twitter application programming interface, using keywords and hashtags sourced through Symplur Signals. Preprocessing involved the removal of hashtags, stop words, and URLs.

Performance of European prediction models for classification of type 1 and type 2 diabetes in Indians.

Aim: We aimed to determine the performance of European prediction models in an Indian population to classify type 1 diabetes(T1D) and type 2 diabetes(T2D).

Methods: We assessed discrimination and calibration of published models of diabetes classification, using retrospective data from electronic medical records of 83309 participants aged 18-50 years living in India. Diabetes type was defined based on C-peptide measurement and early insulin requirement.

Topic modeling and social network analysis approach to explore diabetes discourse on Twitter in India.

Introduction: The utilization of social media presents a promising avenue for the prevention and management of diabetes. To effectively cater to the diabetes-related knowledge, support, and intervention needs of the community, it is imperative to attain a deeper understanding of the extent and content of discussions pertaining to this health issue. This study aims to assess and compare various topic modeling techniques to determine the most effective model for identifying the core themes in diabetes-related tweets, the sources responsible for disseminating this information, the reach of these themes, and the influential individuals within the Twitter community in India.

Detection of hotspots of school dropouts in India: A spatial clustering approach.

School dropout is a significant concern universally. This paper investigates the incorporation of spatial dependency in estimating the topographical effect of school dropout rates in India. This study utilizes the secondary data on primary, upper primary, and secondary school dropout rates of the different districts of India available at the Unified District Information System for Education plus (UDISE+) for the year 2020 to contemplate the impact of these dropouts from one region to different regions in molding with promotion rate and repetition rate.

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.

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.