scholarly journals Quantifying the growth of preprint services hosted by the Center for Open Science

2019 ◽  
Author(s):  
Tom William Narock ◽  
Evan Goldstein
Keyword(s):  
English Language ◽  
Application Programming Interface ◽  
Open Science ◽  
Connected Components ◽  
Connected Component ◽  
Future Studies ◽  
Open Access Journals ◽  
Wide Range ◽  
Application Programming ◽  
Programming Interface

A wide range of disciplines are building preprint services — cyberinfrastructure that enables publishing non peer-reviewed scholarly manuscripts before publication in a peer-reviewed journal. We have quantitatively surveyed nine of the largest English language preprint services offered by the Center for Open Science (COS) and available through the COS Application Programming Interface. All of the services we investigate also permit the submission of postprints, non-typeset versions of peer-reviewed manuscripts. Data indicates that all services are growing, but with submission rates below more mature services (e.g., bioRxiv). The time evolution of the preprint-to-postprint ratio for each service indicates that recent growth is a result of more preprint submissions. The nine COS services we investigate posted papers that appear in a range of peer-reviewed journals, and many of these publication venues are not listed in the Directory of Open Access Journals. As a result, it is likely that the COS services function as open repositories for peer-reviewed papers that would otherwise be behind a paywall. We further analyze the coauthorship network for each COS service, which indicates that the services have many small connected components, and the largest connected component encompasses only a small percentage of total authors on each service. This indicates all services can continue to grow. When comparing the papers submitted to each service, we observe topic overlap measured by keywords self-assigned to each manuscripts, indicating that search functionalities would benefit from cutting across the boundaries of a single service. Finally, though annotation capabilities are integrated into all COS services, it is rarely used by readers. Our analysis of these services can be a benchmark for future studies of preprint service growth.

scholarly journals Quantifying the Growth of Preprint Services Hosted by the Center for Open Science

Publications ◽  
2019 ◽  
Vol 7 (2) ◽  
pp. 44 ◽  
Author(s):  
Tom Narock ◽  
Evan B. Goldstein
Keyword(s):  
English Language ◽  
Application Programming Interface ◽  
Open Science ◽  
Connected Components ◽  
Connected Component ◽  
Web Based ◽  
Open Access Journals ◽  
Wide Range ◽  
Application Programming ◽  
Programming Interface

A wide range of disciplines are building preprint services—web-based systems that enable publishing non peer-reviewed scholarly manuscripts before publication in a peer-reviewed journal. We have quantitatively surveyed nine of the largest English language preprint services offered by the Center for Open Science (COS) and available through an Application Programming Interface. All of the services we investigate also permit the submission of postprints, non-typeset versions of peer-reviewed manuscripts. Data indicates that all services are growing, but with submission rates below more mature services (e.g., bioRxiv). The trend of the preprint-to-postprint ratio for each service indicates that recent growth is a result of more preprint submissions. The nine COS services we investigate host papers that appear in a range of peer-reviewed journals, and many of these publication venues are not listed in the Directory of Open Access Journals. As a result, COS services function as open repositories for peer-reviewed papers that would otherwise be behind a paywall. We further analyze the coauthorship network for each COS service, which indicates that the services have many small connected components, and the largest connected component encompasses only a small percentage of total authors on each service. When comparing the papers submitted to each service, we observe topic overlap measured by keywords self-assigned to each manuscript, indicating that search functionalities would benefit from cutting across the boundaries of a single service. Finally, though annotation capabilities are integrated into all COS services, it is rarely used by readers. Our analysis of these services can be a benchmark for future studies of preprint service growth.

scholarly journals Investigation of university students’ behaviour in a Heterarchical twitter community

2021 ◽  
Author(s):  
Masami Yoshida
Keyword(s):  
University Students ◽  
Application Programming Interface ◽  
Individual Behaviour ◽  
Future Studies ◽  
Social Actors ◽  
Global Issues ◽  
Knowledge Based ◽  
Application Programming ◽  
Programming Interface

AbstractWe conducted an investigational study of the formulation of the heterarchical online knowledge-based community among university students, which also involved users outside a course. As an exercise in a course, students were assigned to post their opinions regarding global issues on Twitter to connect with social actors. The emerging all connections were collected by Twitter’s application programming interface. Dataset was categorised into types of behaviourgraphics, which were styles of online users’ individual behaviour, as proposed by Solis. There were 954 tweets by 197 users, and 13 within 20 types of behaviourgraphics were exhibited in the Twitter community. However, students’ isolated tweets without any connection occupied 74% of all tweets. The tweets of social actors counted for merely 14% of students’ tweets, and connections in the community proved to be sparse. Compared with the types of behaviourgraphics in the results of our previous study, we could identify the following problems in students’ messages: content without relational cues, inhibition points in the content, lack of communicative behaviour, insufficient consideration of timeline, and lack of likeability. The results indicate the need to cultivate students’ sociability skills and their pre-investigation of other communities in order to expand their knowledge-based community. In terms of future studies, we discuss the importance of promoting a bridge to enhance connections with another community.

scholarly journals Using Twitter for sentiment analysis towards AstraZeneca/Oxford, Pfizer/BioNTech and Moderna COVID-19 vaccines

2021 ◽  
pp. postgradmedj-2021-140685
Author(s):  
Robert Marcec ◽  
Robert Likic
Keyword(s):  
Social Media ◽  
Sentiment Analysis ◽  
English Language ◽  
Vaccination Campaign ◽  
Application Programming Interface ◽  
Social Media Platforms ◽  
Application Programming ◽  
Source Of Information ◽  
Programming Interface ◽  
Over Time

IntroductionA worldwide vaccination campaign is underway to bring an end to the SARS-CoV-2 pandemic; however, its success relies heavily on the actual willingness of individuals to get vaccinated. Social media platforms such as Twitter may prove to be a valuable source of information on the attitudes and sentiment towards SARS-CoV-2 vaccination that can be tracked almost instantaneously.Materials and methodsThe Twitter academic Application Programming Interface was used to retrieve all English-language tweets mentioning AstraZeneca/Oxford, Pfizer/BioNTech and Moderna vaccines in 4 months from 1 December 2020 to 31 March 2021. Sentiment analysis was performed using the AFINN lexicon to calculate the daily average sentiment of tweets which was evaluated longitudinally and comparatively for each vaccine throughout the 4 months.ResultsA total of 701 891 tweets have been retrieved and included in the daily sentiment analysis. The sentiment regarding Pfizer and Moderna vaccines appeared positive and stable throughout the 4 months, with no significant differences in sentiment between the months. In contrast, the sentiment regarding the AstraZeneca/Oxford vaccine seems to be decreasing over time, with a significant decrease when comparing December with March (p<0.0000000001, mean difference=−0.746, 95% CI=−0.915 to −0.577).ConclusionLexicon-based Twitter sentiment analysis is a valuable and easily implemented tool to track the sentiment regarding SARS-CoV-2 vaccines. It is worrisome that the sentiment regarding the AstraZeneca/Oxford vaccine appears to be turning negative over time, as this may boost hesitancy rates towards this specific SARS-CoV-2 vaccine.

Noise Corrected Sampling of Online Social Networks

2021 ◽  
Vol 15 (2) ◽  
pp. 1-21
Author(s):  
Michele Coscia
Keyword(s):  
Online Social Networks ◽  
Information Gain ◽  
Application Programming Interface ◽  
Network Sampling ◽  
Topological Network ◽  
Wide Range ◽  
Network Topologies ◽  
Application Programming ◽  
The One ◽  
Programming Interface

In this article, we propose a new method to perform topological network sampling. Topological network sampling is a process for extracting a subset of nodes and edges from a network, such that analyses on the sample provide results and conclusions comparable to the ones they would return if run on whole structure. We need network sampling because the largest online network datasets are accessed through low-throughput application programming interface (API) systems, rendering the collection of the whole network infeasible. Our method is inspired by the literature on network backboning, specifically the noise-corrected backbone. We select the next node to explore by following the edge we identify as the one providing the largest information gain, given the topology of the sample explored so far. We evaluate our method against the most commonly used sampling methods. We do so in a realistic framework, considering a wide array of network topologies, network analysis, and features of API systems. There is no method that can provide the best sample in all possible scenarios, thus in our results section, we show the cases in which our method performs best and the cases in which it performs worst. Overall, the noise-corrected network sampling performs well: it has the best rank average among the tested methods across a wide range of applications.

Sistem Pengawasan Aktifitas Penggunaan Smartphone Android

2018 ◽  
Vol 9 (1) ◽  
pp. 24-31
Author(s):  
Rudianto Rudianto ◽  
Eko Budi Setiawan
Keyword(s):  
Application Programming Interface ◽  
Third Party ◽  
Image Content ◽  
Image File ◽  
Application Programming ◽  
Index Terms ◽  
Programming Interface

Availability the Application Programming Interface (API) for third-party applications on Android devices provides an opportunity to monitor Android devices with each other. This is used to create an application that can facilitate parents in child supervision through Android devices owned. In this study, some features added to the classification of image content on Android devices related to negative content. In this case, researchers using Clarifai API. The result of this research is to produce a system which has feature, give a report of image file contained in target smartphone and can do deletion on the image file, receive browser history report and can directly visit in the application, receive a report of child location and can be directly contacted via this application. This application works well on the Android Lollipop (API Level 22). Index Terms— Application Programming Interface(API), Monitoring, Negative Content, Children, Parent.

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