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Sharing and obtaining information over social media has enabled people to express their opinions regarding any event. Since the tweets regarding the Russia-Ukraine war were extensively publicized on social media, this study aims to analyse the temporal sentiments people express through tweets related to the war.

Relevant hashtag related to the Russia-Ukraine war was identified, and tweets were downloaded using Twitter API, which were later migrated to Orange Data mining software. Pre-processing techniques like transformation, tokenization, and filtering were applied to the extracted tweets. VADER (Valence Aware Dictionary for Sentiment Reasoning) sentiment analysis module of Orange software was used to categorize tweets into positive, negative and neutral ones based on the tweet polarity. For ascertaining the key and co-occurring terms and phrases in tweets and also to visualize the keyword clusters, VOSviewer, a data visualization software, was made use of.

An increase in the number of tweets is witnessed in the initial days, while a decline is observed over time. Most tweets are negative in nature, followed by positive and neutral ones. It is also ascertained that tweets from verified accounts are more impactful than unverified ones. russiaukrainewar, ukraine, russia, false, war, nato, zelensky and stoprussia are the dominant co-occurring keywords. Ukraine, Russia and Putin are the top hashtags for sentiment representation. India, the USA and the UK contribute the highest tweets.

The study tries to explore the public sentiments expressed over Twitter related to Russia-Ukraine war.

The purpose of this study is to determine the funding ratio of BRICS nations in various research areas. The leading funding institutions that support research in the developing world have also been researched.

This study involves the funding acknowledgment analysis of the data retrieved from the “Clarivate Analytics' InCites database” under “22 specific research areas” to determine whether the publication was funded.

This study shows that China achieves the highest funding ratio of 88.6%, followed by Brazil (73.74%), Russia (72.93%) and South Africa (70.94%). However, India has the lowest funding ratio of 58.2%. For the subject areas, the highest funding ratio is by microbiology in Russia (86.6%), India (84.3%) and China (96.9%) and space science in Brazil (93.7%) and South Africa (94.82%). However, economics and business achieves the lowest funding ratio in Brazil (38.6%), India (20.1%) and South Africa (30.24%). Moreover, the regional funding agencies are the leading research sponsors in the BRICS nations.

This study implies increasing the funding ratio across various research areas, including arts, humanities and social sciences. The nations, particularly India, also need to gear up sponsoring the research to improve the funding ratio for scientific development, bringing overall good.

This study efforts to show the status of countries and research subjects in terms of funding ratio and reveals the prominent funders working toward scientific growth.

The study aims to shed light on the current state of “Dataset repositories” indexed in Directory of Open Access Repositories (OpenDOAR).

From each repository/record information, the Open-Access Policies, Open Archives Initiative Protocol for Metadata Harvesting (OAI-PMH), year of creation and the number of data sets archived in the repositories were manually searched, documented and analyzed.

Developed countries like the United Kingdom and the USA are primarily involved in the development of institutional open-access repositories comprising significant components of OpenDOAR. The most extensively used software is DSpace. Most data set archives are OAI-PMH compliant but do not follow open-access rules. The study also highlights the sites’ embrace of Web 2.0 capabilities and discovers really simple syndication feeds and Atom integration. The use of social media has made its presence known. Furthermore, the study concludes that the number of data sets kept in repositories is insufficient, although the expansion of such repositories has been consistent over the years.

The work has the potential to benefit both researchers in general and policymakers in particular. Scholars interested in research data, data sharing and data reuse can learn about the present state of repositories that preserve data sets in OpenDOAR. At the same time, policymakers can develop recommendations and policies to assist in the construction and maintenance of repositories for data sets.

According to the literature, there have been numerous studies on open-access repositories and OpenDOAR internationally, but no research has focused on repositories preserving content-type data sets. As a result, the study attempts to uncover various characteristics of OpenDOAR Data set repositories.