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The study aims to showcase public sentiments via social media, Twitter, during 2014 floods of Jammu and Kashmir, India.

The study is based on content analysis of tweets related to Kashmir floods. Search was performed with “#kashmirfloods” and was confined to tweets posted from 4 September 2014 through 3 November 2014. A naturalistic approach was applied to examine the content and classify tweets into 5 major and 25 sub categories. Data as such collected were tabulated in SPSS 21 for analysis.

During the study period, individuals, news channels, and organisations posted a total of 36,697 tweets related to Kashmir floods. It all started with an outburst of tweets which goes on declining (exponentially) with every passing day. People express themselves in a number of ways with informational tweets used more during the time of disaster. Individuals expressing their sentiments outscore other types of sentiments with text-based tweets ranking high. About 44 per cent of tweets were retweeted, and nearly 31 per cent tweets were marked favourite. Comparatively, more number of informational and help tweets were retweeted or marked favourite. Contextual richness of tweet (i.e. number of embedded expressions) enhances its visibility by means of getting liked and/or retweeted. A statistically significant positive association is observed between the number of expressions in a tweet and the number of times it is liked (favourite) or retweeted.

Twitter plays a pivotal role during natural calamities like Kashmir floods to connect people in the hour of need and help. It provides a platform where the plight of people is heard across the globe and which encourages people to unite and overcome hurdles together.

This study examines the sentiments of people expressed during Jammu and Kashmir (India) Floods 2014 on social media – Twitter.

The purpose of the study is to analyze the impact of the Publication Timeline, i.e. Submission to First Decision and Submission to Acceptance on Journal Metrics, i.e. Impact Factor (IF) and 5-year IF.

Data related to the IF and 5-year IF were retrieved from Clarivate Analytics’ Journal Citation Report 2020. The Publication Timeline of each journal was ascertained through their respective websites. To attain the model fit summary, an analysis of variance (ANOVA) test was performed. Regression analysis was also performed on the models using SPSS 21 software to ascertain the nature and degree of impact the Publication Timeline (Submission to First Decision and Submission to Acceptance) has on Journal Metrics (IF and 5-year IF).

Submission to First Decision has a significant inverse relationship with both the IF and 5-year IF, whereas Submission to Acceptance has a significant direct relation with 5-year IF and an inverse but insignificant relationship with IF.

Journals published by Springer Nature and of multidisciplinary nature have been considered for the study. Only those journals were selected that provided the information regarding the Publication Timeline, whereas those which did not provide the same, were excluded. However, new insights can be revealed if the journals published by different publishers and belonging to one particular discipline are studied.

The study helps to ascertain the impact of the Publication Timeline on the Impact Metrics of the journals. It can help the authors select the journals as their publishing venues considering the Publication Timeline. Publishers can also be benefitted from the findings of this study since improvisations and modifications in their Publication Timelines can positively influence the impact metrics of their respective journals.

The study attempts to measure the impact of the Publication Timeline on Journal Metrics using cross-sectional secondary data, by performing regression analysis. Though various studies have examined the influence of the Publication Timeline on the IF using correlation analysis, to the best of the authors’ knowledge, this study is the first of its kind to use regression analysis to check the relation, as well as the degree of impact the Publication Timeline, has on Journal Metrics.

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.

This study aims to showcase the effect of gender in the field of library and information science.

Research and review articles published from 2005 through 2014 in The Electronic Library, a prominent journal in the field of Library and Information Science, were examined from the perspective of authors’ gender. Influence of gender was assessed with respect to at individual and collaborative levels, quality in terms of citedness and citation count, and receipt of research grants.

There has been an increase in the proportion of male authors over the years with a resulting decline in female authors. Male authors are more productive as teachers, while females contribute more as working professionals or while they peruse their academic/research programmes. Though the productivity in collaborative works has increased in all gender combinations, it is more prominent when authors of opposite gender team up. No significant difference is observed in the number of national or international works produced in different collaborative authorship patterns. There is no difference in the number of male and female authors in male–female collaborative works. Works sponsored by grants are produced more frequently in groups comprising male–female or male–male members. No significant difference is observed in the number of cited or uncited works produced in different authorship patterns. The number of citations to works is independent of the nature of gender-wise authorship patterns.

The study examines the status of women in research, specifically in the field of library and information science. The findings of the study are based on the contribution of the authors involved with the journal, “The Electronic Library”. Readers are encouraged to expand the study by including authors that contribute to other library and information science journals.

The study is first of its kind to highlight the involvement and observe the influence of female authors in the field of library and information science research.

Open access journals (OAJs) offer immediate, free and unrestricted online access to the scholarly literature. The purpose of this study is to trace the status and characteristics of OAJs published across the globe. Various trends that have evolved in OAJ market have been studied.

The study is based on data collected from one of the largest OA journal directory – Directory of Open Access Journals (DOAJ). The data were downloaded on 02 January 2018 and details of OAJs added to DOAJ till 31 December 2018 were harvested, codified and further analyzed in SPSS software. A Microsoft-Excel template application – MAKESENS – developed by Finnish Meteorological Institute (Finland) in 2002, was explored to perform Mann–Kendall Test and Sen’s Slope Estimates.

A less score of OAJs offer access to their archival content. An increasing trend is witnessed in the OAJ publishing with Elsevier, Sciendo and BioMed Central (BMC) as the top publishers. Majority of publishers are from high-income zone countries, followed by upper-middle and lower-middle zone countries. Majority of OA publishers are from the UK, Indonesia and Brazil. A lesser score of journals offer article processing charges and/or author submission charges. Majority of OAJs from high- and lower-middle-income zone countries levy submission/processing charge to authors compared to OA journals from upper-middle- and lower-income zone countries (p < 0.01). OJS stays a prioritized platform for hosting OA journal content. Portico and CLOCKSS/LOCKSS are mostly used for long-term preservation purposes. Majority of OAJs from high-income zone countries participate in digital arching initiatives compared to ones from other income zones. Majority of the journals adopt a peer review (double-blind peer review, blind peer review, peer review and open peer review) process for validation of their scholarly content. The time lag between submission and publication ranges from one to 53 weeks, with majority of OAJs having a time lag of 11-20 weeks. Creative Commons Licenses are mainly adopted by OAJs.

As the study is based on the data offered by DOAJ, any gaps in the DOAJ data will also get reflected in the study. Further, there might be other OAJs also that have yet to show compliance with DOAJ standards and get indexed with it.

The study tries to showcase the current status and characteristics of OAJs.

The purpose of the study is to evaluate the relationship of Journal Publication Timeline (submission to first decision and submission to final decision) with various Journal Metrics (citing half-life, article influence score, the immediacy index, the acceptance rate, the impact factor (IF), five years IF, Eigenfactor and cited half-life) of top 600 journals retrieved from Journal Citation Report (JCR) 2020 under the tag, Elsevier Unified.

Top 600 journals in the decreasing order of the IFs under the tag, “Elsevier Unified” were retrieved from JCR 2020 of Clarivate Analytics. Information about “Journal Metrics” was ascertained using “Customized Service” of JCR, while information about the “Publication Timeline” of each journal was obtained using Elsevier's “Journal Insights Service.” It was found that only 177 journals provided the complete information regarding the “Publication Timeline” and hence considered for the study. Descriptive statistics and correlation analysis was conducted to test the different hypotheses.

It was found that submission to first decision has a significant relationship with the immediacy index, citing half-life and the acceptance rate. Submission to final decision has a significant relationship with Journal Impact Factor (JIF), the immediacy index, Eigenfactor, citing half-life and the acceptance rate.

The study will provide the authors with sound and valuable information to support their selection of journals. Inferences in light of fluctuations in the scholarly communication process in terms of Publication Timelines and Journal Metrics can be deeply understood with the aid of the current study's findings. What considerations authors have to take before submitting their papers is the main implication of the study. Journal administrators can also benefit from the findings of the current study as it can help recruit and manage reviewers, which will ensure a successful publication timeline.

The study correlates Publication Timeline Indicators with Journal Metrics Indicators using secondary cross-sectional data. Though most previous studies only examine the relationship of the Publication Timeline with the Journal Impact Factor (JIF), there is very scarce literature that deciphers the influence of Publication Timeline indicators on different Journal Metrics indicators (including JIF).

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-02-2022-0108.

Twitter as a social tool allows people to express their views, emotions or communicate information within brevity of 140 character limit. It has provided an opportunity to researchers to tab users’ expressions on social or political issues, be it natural calamity, elections and alike. The purpose of this paper is to assess how people explored Twitter to express their views regarding state assembly elections of Jammu and Kashmir (India).

The authors performed content analysis of 4,537 tweets that were posted by 1,420 different Twitter users over a period of 78 days (October 30, 2014 through January 15, 2015).

Users were found to be active on the days of polling while post-polling period witnessed a huge influx in particular on the day of voting and declaration of results. Nearly 94 percent users have posted around 50 percent of tweets and there were only 81 handles which posted remaining 50 percent tweets. In additions to people, news agencies, anonymous groups and social/political groups have expressed their views on this event. Nearly one-fourth tweets were retweeted and one-fourth tweets were marked favorite. Users have mostly providing news updates or personnel commentaries about the election process.

The study is first of its kind using Twitter to represent the sentiments of people during floods.

The purpose of this study is to assess the retrieval performance of three search engines, i.e. Google, Yahoo and Bing for navigational queries using two important retrieval measures, i.e. precision and relative recall in the field of life science and biomedicine.

Top three search engines namely Google, Yahoo and Bing were selected on the basis of their ranking as per Alexa, an analytical tool that provides ranking of global websites. Furthermore, the scope of study was confined to those search engines having interface in English. Clarivate Analytics' Web of Science was used for the extraction of navigational queries in the field of life science and biomedicine. Navigational queries (classified as one-word, two-word and three-word queries) were extracted from the keywords of the papers representing the top 100 contributing authors in the select field. Keywords were also checked for the duplication. Two important evaluation parameters, i.e. precision and relative recall were used to calculate the performance of search engines on the navigational queries.

The mean precision for Google scores high (2.30) followed by Yahoo (2.29) and Bing (1.68), while mean relative recall also scores high for Google (0.36) followed by Yahoo (0.33) and Bing (0.31) respectively.

The study is of great help to the researchers and academia in determining the retrieval efficiency of Google, Yahoo and Bing in terms of navigational query execution in the field of life science and biomedicine. The study can help users to focus on various search processes and the query structuring and its execution across the select search engines for achieving desired result list in a professional search environment. The study can also act as a ready reference source for exploring navigational queries and how these queries can be managed in the context of information retrieval process. It will also help to showcase the retrieval efficiency of various search engines on the basis of subject diversity (life science and biomedicine) highlighting the same in terms of query intention.

Though many studies have been conducted highlighting the retrieval efficiency of search engines the current work is the first of its kind to study the retrieval effectiveness of Google, Yahoo and Bing on navigational queries in the field of life science and biomedicine. The study will help in understanding various methods and approaches to be adopted by the users for the navigational query execution across a professional search environment, i.e. “life science and biomedicine”

The purpose of this paper is to assess the influence of personality traits on perception and acceptance of open access (OA) mode of publishing by the author community of University of Kashmir, India. The study is an attempt to highlight the relationship between personality traits of authors and OA mode of publishing.

The study is based on the responses of 48 faculty members affiliated with different Departments of Science Discipline of University of Kashmir. Big Five personality traits (extraversion, agreeableness, conscientiousness, emotional stability and openness to experience) were tapped through ten-item personality inventory, and information regarding OA was gauged through six self-devised statements.

Pearson correlation test confirms statistically significant relation between personality traits and different dimensions of OA mode of publishing. Personality traits are found to have an influence on author’s perception of OA mode of publishing. However, the study could not ascertain any relation between the notions of an author about the quality of OA content with any of the personality traits. Emotionally stable authors are found to explicitly submit their work in OA journals without any anxiety or negativity. Agreeable and conscientious authors also prefer to keep their work open to make it helpful to the broader audience and get maximum recognition from peers and citations to their work respectively. However, some authors (agreeable) hesitate in submitting their work in open platforms due to the fear of getting their works easily copied.

The study is first of its kind highlighting a new dimension in the field of OA and investigates the influence of personality traits on author’s attitude towards open mode of publishing.

The purpose of this study is to explore the retrieval effectiveness of three image search engines (ISE) – Google Images, Yahoo Image Search and Picsearch in terms of their image retrieval capability. It is an effort to carry out a Cranfield experiment to know how efficient the commercial giants in the image search are and how efficient an image specific search engine is.

The keyword search feature of three ISEs – Google images, Yahoo Image Search and Picsearch – was exploited to make search with keyword captions of photos as query terms. Selected top ten images were used to act as a testbed for the study, as images were searched in accordance with features of the test bed. Features to be looked for included size (1200 × 800), format of images (JPEG/JPG) and the rank of the original image retrieved by ISEs under study. To gauge the overall retrieval effectiveness in terms of set standards, only first 50 result hits were checked. Retrieval efficiency of select ISEs were examined with respect to their precision and relative recall.

Yahoo Image Search outscores Google Images and Picsearch both in terms of precision and relative recall. Regarding other criteria – image size, image format and image rank in search results, Google Images is ahead of others.

The study only takes into consideration basic image search feature, i.e. text-based search.

The study implies that image search engines should focus on relevant descriptions. The study evaluated text-based image retrieval facilities and thereby offers a choice to users to select best among the available ISEs for their use.

The study provides an insight into the effectiveness of the three ISEs. The study is one of the few studies to gauge retrieval effectiveness of ISEs. Study also produced key findings that are important for all ISE users and researchers and the Web image search industry. Findings of the study will also prove useful for search engine companies to improve their services.