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.

User identification across online social networks in practice: Pitfalls and solutions

2016 ◽  
Vol 44 (3) ◽  
pp. 377-391 ◽  
Author(s):  
Azadeh Esfandyari ◽  
Matteo Zignani ◽  
Sabrina Gaito ◽  
Gian Paolo Rossi
Keyword(s):  
Social Networks ◽  
Online Social Networks ◽  
Full Range ◽  
Application Programming Interface ◽  
User Identification ◽  
Application Programming ◽  
Test Sets ◽  
Set Up ◽  
Different Levels ◽  
Programming Interface

To take advantage of the full range of services that online social networks (OSNs) offer, people commonly open several accounts on diverse OSNs where they leave lots of different types of profile information. The integration of these pieces of information from various sources can be achieved by identifying individuals across social networks. In this article, we address the problem of user identification by treating it as a classification task. Relying on common public attributes available through the official application programming interface (API) of social networks, we propose different methods for building negative instances that go beyond usual random selection so as to investigate the effectiveness of each method in training the classifier. Two test sets with different levels of discrimination are set up to evaluate the robustness of our different classifiers. The effectiveness of the approach is measured in real conditions by matching profiles gathered from Google+, Facebook and Twitter.

scholarly journals Why Experimental Interfaces Should Include an Application Programming Interface

2015 ◽  
Vol 6 (2) ◽  
Author(s):  
Stan Ruecker ◽  
Peter Hodges ◽  
Nayaab Lokhadwala ◽  
Szu-Ying Ching ◽  
Jennifer Windsor ◽  
...  
Keyword(s):  
Application Programming Interface ◽  
The Other ◽  
Computer Interfaces ◽  
Human Computer Interfaces ◽  
Application Programming ◽  
Boolean Queries ◽  
Visual Construction ◽  
The One ◽  
Programming Interface

An Application Programming Interface (API) can serve as a mechanism for separating interface concerns on the one hand from data and processing on the other, allowing for easier implementation of alternative human-computer interfaces. The API can also be used as a sounding board for ideas about what an interface should and should not accomplish. Our discussion will take as its case study our recent work in designing experimental interfaces for the visual construction of Boolean queries, for a project we have previously called the Mandala Browser.

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 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.

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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