A Comprehensive Review of Professional Network Impact on Education and Career

2021 ◽  
pp. 1-26
Author(s):  
Calin Constantinov ◽  
Mihai L. Mocanu
Keyword(s):  
Social Networks ◽  
Real World ◽  
Data Privacy ◽  
Modern World ◽  
Minimal Effect ◽  
Research Papers ◽  
Professional Networks ◽  
Comprehensive Review ◽  
Research Areas ◽  
Professional Network

In their very beginnings, when social networks were solely used for leisure purposes, any action performed online had minimal effect on the real world lives of their members. This has very much changed in our modern world, where becoming an influencer on Instagram can substantially raise one's income, politics is done on Twitter, and an inappropriate video posted on YouTube can get one fired. Similarly, professional networks have changed the approach universities take to prepare their students, the mechanisms behind companies seeking expertise, and the way in which professionals land matching jobs. In the context of discussing the benefits and pitfalls of using such platforms, several points relating to data privacy are highlighted. Additionally, for a complete view of all analytics possibilities, a survey was conducted by looking over 24 research papers, summarising their findings, detailing the six generic research areas which were identified and speculating on what the future might hold.

A Survey on Overlapping Communities in Large-Scale Social Networks

2018 ◽  
pp. 198-215
Author(s):  
S Rao Chintalapudi ◽  
H. M. Krishna Prasad M
Keyword(s):  
Social Networks ◽  
Community Detection ◽  
Biological Networks ◽  
Modern World ◽  
Overlapping Community Detection ◽  
Overlapping Communities ◽  
Detection Algorithms ◽  
Research Areas ◽  
Network Generator ◽  
Overlapping Community

Social network analysis is one of the emerging research areas in the modern world. Social networks can be adapted to all the sectors by using graph theory concepts such as transportation networks, collaboration networks, and biological networks and so on. The most important property of social networks is community, collection of nodes with dense connections inside and sparse connections at outside. Community detection is similar to clustering analysis and has many applications in the real-time world such as recommendation systems, target marketing and so on. Community detection algorithms are broadly classified into two categories. One is disjoint community detection algorithms and the other is overlapping community detection algorithms. This chapter reviews overlapping community detection algorithms with their strengths and limitations. To evaluate these algorithms, a popular synthetic network generator, i.e., LFR benchmark generator and the new extended quality measures are discussed in detail.

Management in Social and Professional Networks

Upravlenie ◽  
2015 ◽  
Vol 3 (3) ◽  
pp. 68-72
Author(s):  
Колесников ◽  
M. Kolesnikov ◽  
Киба ◽  
M. Kiba
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Mass Distribution ◽  
Graph Model ◽  
Point Of View ◽  
Analytical Representation ◽  
Opinion Formation ◽  
Professional Networks ◽  
Professional Network

The extended idea about “professional network” has been developed based on the concept of “social network”. The main features and tasks of professional social networks have been revealed. The task of management in social and professional networks which demanded formalization of criteria and models of their functioning has been set. Professional social network has been represented as a graph model. Known models of influence in social and professional networks have been considered and described in detail from the point of view of their analytical representation. The main features of professional networks influence on society and production have been revealed. Possibility for mass distribution of information by means of professional social networks has been analyzed. A mechanism for network agents’ opinion formation on the basis of authoritative opinion and a trust vector has been revealed.

Borders, Conflicts and Bargaining in Federations and Communities of Governments

2009 ◽  
pp. 83-99
Author(s):  
A. Libman
Keyword(s):  
Economic Policy ◽  
Public Authority ◽  
Modern World ◽  
Main Research ◽  
Research Areas ◽  
Nation States ◽  
Distribution Of Power

Economic policy in the modern world can be treated as an outcome of interaction of multiple territorial centers of public authority: nation-states, subnational and supranational jurisdictions. In the last decades economics has increased its attention to the factors which influence the distribution of power among jurisdictions. The paper surveys two main research areas in this literature: economics of conflicts and theory of endogenous decentralization. It discusses the basic models of both approaches and their modifications applied in the literature as well as factors of conflict formation and bargaining over devolution.

Phytochemical and Pharmacological Review on Two Herbs of Baijiangcao: Patrinia scabiosaefolia Fisch. ex Trev. and Patrinia villosa (Thunb.) Juss

2020 ◽  
Vol 17 (5) ◽  
pp. 496-517
Author(s):  
Yangcheng Liu ◽  
Wei Liu ◽  
Jiaqi Wang ◽  
Yang Liu ◽  
Changlan Chen ◽  
...  
Keyword(s):  
Chemical Constituents ◽  
Volatile Components ◽  
Research Papers ◽  
Pharmacological Activities ◽  
Comprehensive Review ◽  
Scientific Databases ◽  
The Past ◽  
Current State ◽  
Patrinia Scabiosaefolia ◽  
Antiviral Activities

Patrinia scabiosaefolia Fisch. Trev. and Patrinia villosa (Thunb.) Juss, are two species of Patrinia recorded in the Chinese Pharmacopoeia with the same Chinese name “Baijiangcao” and similar therapeutic effect in traditional Chinese medicine. The present article is the first comprehensive review on the chemical composition and pharmacological activities of these herbs. In this review, data on chemical constituents and pharmacological profile of the two herbs are provided. This review discusses all the classes of the 223 compounds (phenylpropanoids, flavonoids, terpenes, saponins and volatile components, etc.) detected in the two herbs providing information on the current state of knowledge of the phytochemicals present in them. In the past three years, our research group has isolated and identified about more than 100 ingredients from the two herbs. Therefore, we published a systematic review of our research papers and studies on the two herbs were carried out using resources such as classic books about Chinese herbal medicine and scientific databases including Pubmed, Web of Science, SciFinder, CNKI. etc. The present review discusses the most thoroughly studied pharmacological activities (antioxidant, anti-inflammatory, immunomodulatory, antimicrobial, antitumor and antiviral activities) of the two herbs. This comprehensive review will be informative for scientists searching for new properties of these herbs and will be important and significant for the discovery of bioactive compounds from the two herbs and in complete utilization of Patrinia scabiosaefolia Fisch. ex Trev. and Patrinia villosa (Thunb.) Juss.

Systems theories

2018 ◽  
Author(s):  
Marc J. Stern
Keyword(s):  
Social Networks ◽  
Problem Solving ◽  
Natural Resources ◽  
Real World ◽  
Common Pool Resources ◽  
Ecological Systems ◽  
Effective Governance ◽  
Social Ecological Systems ◽  
Social Ecological ◽  
Real World Problem

This chapter covers systems theories relevant to understanding and working to enhance the resilience of social-ecological systems. Social-ecological systems contain natural resources, users of those resources, and the interactions between each. The theories in the chapter share lessons about how to build effective governance structures for common pool resources, how to facilitate the spread of worthwhile ideas across social networks, and how to promote collaboration for greater collective impacts than any one organization alone could achieve. Each theory is summarized succinctly and followed by guidance on how to apply it to real world problem solving.

Solving the Internet Jurisdiction Puzzle

2017 ◽  
Author(s):  
Dan Jerker B. Svantesson
Keyword(s):  
International Law ◽  
Cyber Security ◽  
Data Privacy ◽  
Modern World ◽  
The Internet ◽  
Private International Law ◽  
Reform Initiatives ◽  
Legal Principles ◽  
Privacy Law ◽  
History Of

Internet jurisdiction has emerged as one of the greatest and most urgent challenges online, severely affecting areas as diverse as e-commerce, data privacy, law enforcement, content take-downs, cloud computing, e-health, Cyber security, intellectual property, freedom of speech, and Cyberwar. In this innovative book, Professor Svantesson presents a vision for a new approach to Internet jurisdiction––for both private international law and public international law––based on sixteen years of research dedicated specifically to the topic. The book demonstrates that our current paradigm remains attached to a territorial thinking that is out of sync with our modern world, especially, but not only, online. Having made the claim that our adherence to the territoriality principle is based more on habit than on any clear and universally accepted legal principles, Professor Svantesson advances a new jurisprudential framework for how we approach jurisdiction. He also proposes several other reform initiatives such as the concept of ‘investigative jurisdiction’ and an approach to geo-blocking, aimed at equipping us to solve the Internet jurisdiction puzzle. In addition, the book provides a history of Internet jurisdiction, and challenges our traditional categorisation of different types of jurisdiction. It places Internet jurisdiction in a broader context and outlines methods for how properly to understand and work with rules of Internet jurisdiction. While Solving the Internet Puzzle paints a clear picture of the concerns involved and the problems that needs to be overcome, this book is distinctly aimed at finding practical solutions anchored in a solid theoretical framework.

scholarly journals Optimization Algorithms for Detection of Social Interactions

Algorithms ◽  
2020 ◽  
Vol 13 (6) ◽  
pp. 139 ◽  
Author(s):  
Vincenzo Cutello ◽  
Georgia Fargetta ◽  
Mario Pavone ◽  
Rocco A. Scollo
Keyword(s):  
Social Networks ◽  
Local Search ◽  
Social Interactions ◽  
Community Detection ◽  
Experimental Analysis ◽  
Search Strategy ◽  
Random Search ◽  
Optimization Methods ◽  
Research Areas ◽  
Greedy Optimization

Community detection is one of the most challenging and interesting problems in many research areas. Being able to detect highly linked communities in a network can lead to many benefits, such as understanding relationships between entities or interactions between biological genes, for instance. Two different immunological algorithms have been designed for this problem, called Opt-IA and Hybrid-IA, respectively. The main difference between the two algorithms is the search strategy and related immunological operators developed: the first carries out a random search together with purely stochastic operators; the last one is instead based on a deterministic Local Search that tries to refine and improve the current solutions discovered. The robustness of Opt-IA and Hybrid-IA has been assessed on several real social networks. These same networks have also been considered for comparing both algorithms with other seven different metaheuristics and the well-known greedy optimization Louvain algorithm. The experimental analysis conducted proves that Opt-IA and Hybrid-IA are reliable optimization methods for community detection, outperforming all compared algorithms.

scholarly journals CSO Classifier 3.0: a scalable unsupervised method for classifying documents in terms of research topics

2021 ◽  
Author(s):  
Angelo Salatino ◽  
Francesco Osborne ◽  
Enrico Motta
Keyword(s):  
Computer Science ◽  
Digital Libraries ◽  
Gold Standard ◽  
Research Trends ◽  
Alternative Methods ◽  
Relevant Research ◽  
Research Topics ◽  
Research Papers ◽  
Research Areas ◽  
Unsupervised Approach

AbstractClassifying scientific articles, patents, and other documents according to the relevant research topics is an important task, which enables a variety of functionalities, such as categorising documents in digital libraries, monitoring and predicting research trends, and recommending papers relevant to one or more topics. In this paper, we present the latest version of the CSO Classifier (v3.0), an unsupervised approach for automatically classifying research papers according to the Computer Science Ontology (CSO), a comprehensive taxonomy of research areas in the field of Computer Science. The CSO Classifier takes as input the textual components of a research paper (usually title, abstract, and keywords) and returns a set of research topics drawn from the ontology. This new version includes a new component for discarding outlier topics and offers improved scalability. We evaluated the CSO Classifier on a gold standard of manually annotated articles, demonstrating a significant improvement over alternative methods. We also present an overview of applications adopting the CSO Classifier and describe how it can be adapted to other fields.

scholarly journals Evaluating Professional Networks in a Gerontological Pre-Dissertation Initiative Using Social Network Analysis

2020 ◽  
Vol 4 (Supplement_1) ◽  
pp. 549-550
Author(s):  
Erin Murphy ◽  
Rebecca Mauldin ◽  
Jennifer Greenfield ◽  
Nancy Kusmaul ◽  
Noelle Fields ◽  
...  
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Early Career ◽  
Professional Relationships ◽  
Professional Networks ◽  
Professional Needs ◽  
Early Career Faculty ◽  
Professional Network ◽  
Conference Presentations

Abstract Professional networks are critical for PhD students and early career faculty, yet there is scant research on the development of their professional networks. Social network analysis is a useful approach to describe the development of professional networks. This methodological paper explains its use and benefits, using a social network analysis of alumni from the first three cohorts of the Association of Gerontological Education in Social Work (AGESW)’s Pre-Dissertation Fellowship Program (PDFP) as an example. We present results, challenges, and recommendations. Alumni (n = 12) reported meeting an average of 20 scholars (SD = 13.2) through AGESW. These professional relationships led to collaborations on conference presentations and manuscripts as well as opportunities to leverage the relationships for future professional needs. Suggested applications of social network analysis for program evaluation, such as co-author and citation networks, are also presented with a focus on training programs designed to support robust professional network development.

Review Summary Generation in Online Systems: Frameworks for Supervised and Unsupervised Scenarios

2021 ◽  
Vol 15 (3) ◽  
pp. 1-33
Author(s):  
Wenjun Jiang ◽  
Jing Chen ◽  
Xiaofei Ding ◽  
Jie Wu ◽  
Jiawei He ◽  
...  
Keyword(s):  
Decision Making ◽  
Real World ◽  
Text Summarization ◽  
Experimental Results ◽  
Product Review ◽  
Comprehensive Review ◽  
Online Systems ◽  
Real World Datasets ◽  
Different Characteristics

In online systems, including e-commerce platforms, many users resort to the reviews or comments generated by previous consumers for decision making, while their time is limited to deal with many reviews. Therefore, a review summary, which contains all important features in user-generated reviews, is expected. In this article, we study “how to generate a comprehensive review summary from a large number of user-generated reviews.” This can be implemented by text summarization, which mainly has two types of extractive and abstractive approaches. Both of these approaches can deal with both supervised and unsupervised scenarios, but the former may generate redundant and incoherent summaries, while the latter can avoid redundancy but usually can only deal with short sequences. Moreover, both approaches may neglect the sentiment information. To address the above issues, we propose comprehensive Review Summary Generation frameworks to deal with the supervised and unsupervised scenarios. We design two different preprocess models of re-ranking and selecting to identify the important sentences while keeping users’ sentiment in the original reviews. These sentences can be further used to generate review summaries with text summarization methods. Experimental results in seven real-world datasets (Idebate, Rotten Tomatoes Amazon, Yelp, and three unlabelled product review datasets in Amazon) demonstrate that our work performs well in review summary generation. Moreover, the re-ranking and selecting models show different characteristics.

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