scholarly journals A Survey of Information Cascade Analysis

2021 ◽  
Vol 54 (2) ◽  
pp. 1-36
Author(s):  
Fan Zhou ◽  
Xovee Xu ◽  
Goce Trajcevski ◽  
Kunpeng Zhang
Keyword(s):  
Information Diffusion ◽  
Research Work ◽  
Viral Marketing ◽  
Graph Representation ◽  
Digital Information ◽  
Information Cascades ◽  
Challenges And Opportunities ◽  
Scientific Papers ◽  
Popularity Prediction ◽  
Types Of Information

The deluge of digital information in our daily life—from user-generated content, such as microblogs and scientific papers, to online business, such as viral marketing and advertising—offers unprecedented opportunities to explore and exploit the trajectories and structures of the evolution of information cascades. Abundant research efforts, both academic and industrial, have aimed to reach a better understanding of the mechanisms driving the spread of information and quantifying the outcome of information diffusion. This article presents a comprehensive review and categorization of information popularity prediction methods, from feature engineering and stochastic processes , through graph representation , to deep learning-based approaches . Specifically, we first formally define different types of information cascades and summarize the perspectives of existing studies. We then present a taxonomy that categorizes existing works into the aforementioned three main groups as well as the main subclasses in each group, and we systematically review cutting-edge research work. Finally, we summarize the pros and cons of existing research efforts and outline the open challenges and opportunities in this field.

Agricultural research reclamation in Ukraine: Professor D.O. Dzhovani (1886–1971)

2020 ◽  
Author(s):  
V. Verhunov ◽  
Yu. Dovgoruk
Keyword(s):  
Agricultural Land ◽  
Land Reclamation ◽  
Agricultural Research ◽  
Research Work ◽  
Agricultural Science ◽  
Research Network ◽  
Scientific Papers ◽  
Archival Documents ◽  
Active Interest ◽  
Agricultural Schools

The monograph highlights the main stages of development of agricultural research land reclamation work in Ukraine, one of the founders, creators and developers of which was Professor D.O. Dzhovani. The scientific, scientific-organizational and pedagogical activities of the well-known domestic scientist was described, who is an iconic figure for the formation of experimental reclamation work in Ukraine and abroad. The professor laid the scientific-organizational and conceptual principles, in particular the state legislative acts of development of the scientific direction of agro-amelioration in Ukraine and Russia during the 20-30's of the 20th century. He is the author of a number of scientific papers in the field of experimental land reclamation, author of the first textbook in Ukrainian for agricultural courses "Reclamation legislation: a guide for the agricultural schools"(1927). D.O. Dzhovani was personally involved in the opening of a number of reclamation stations in the research network of Ukraine. He was a member of the Scientific & Advisory Board (SAB) on the construction of Dniprelstan and the Special Commission on Dniprelstan at the Agricultural Scientific Committee of Ukraine. The scientist is one of the founders of the Ukrainian Scientific & Research Institute of Agricultural Land Reclamation. The available archival documents attest to his significant contribution to the establishment and subsequent functioning of this institution. After forced emigration to Great Britain, he continued to supplement his inventions and research in the field of agriculture, until the end of his days he did not lose active interest in the business of his life – land reclamation and swamp culture. This edition also contains bibliographic descriptions of his works, written personally and in co-authorship, reports on scientific activities, scientific & popular publications. The book is recommended for scientists, teachers, graduate students, students, specialists in agricultural science, all those who are interested in the history of agricultural research work development.

scholarly journals Recommender systems in model-driven engineering

2021 ◽  
Author(s):  
Lissette Almonte ◽  
Esther Guerra ◽  
Iván Cantador ◽  
Juan de Lara
Keyword(s):  
Recommender Systems ◽  
Information Filtering ◽  
Research Work ◽  
Model Driven Engineering ◽  
Video Broadcasting ◽  
Model Driven ◽  
Challenges And Opportunities ◽  
Mapping Review ◽  
Development Processes ◽  
Systematic Mapping Review

AbstractRecommender systems are information filtering systems used in many online applications like music and video broadcasting and e-commerce platforms. They are also increasingly being applied to facilitate software engineering activities. Following this trend, we are witnessing a growing research interest on recommendation approaches that assist with modelling tasks and model-based development processes. In this paper, we report on a systematic mapping review (based on the analysis of 66 papers) that classifies the existing research work on recommender systems for model-driven engineering (MDE). This study aims to serve as a guide for tool builders and researchers in understanding the MDE tasks that might be subject to recommendations, the applicable recommendation techniques and evaluation methods, and the open challenges and opportunities in this field of research.

scholarly journals A study on sequential pattern mining on chemical information

2018 ◽  
Vol 7 (3.3) ◽  
pp. 532
Author(s):  
S Sathya ◽  
N Rajendran
Keyword(s):  
Data Mining ◽  
Chemical Bonding ◽  
Sequential Analysis ◽  
Pattern Mining ◽  
Fundamental Problem ◽  
Research Work ◽  
Sequential Pattern Mining ◽  
Sequential Pattern ◽  
Graph Representation ◽  
Chemical Information

Data mining (DM) is used for extracting the useful and non-trivial information from the large amount of data to collect in many and diverse fields. Data mining determines explanation through clustering visualization, association and sequential analysis. Chemical compounds are well-defined structures compressed by a graph representation. Chemical bonding is the association of atoms into molecules, ions, crystals and other stable species which frame the common substances in chemical information. However, large-scale sequential data is a fundamental problem like higher classification time and bonding time in data mining with many applications. In this work, chemical structured index bonding is used for sequential pattern mining. Our research work helps to evaluate the structural patterns of chemical bonding in chemical information data sets.  

Comparing information diffusion mechanisms by matching on cascade size

2021 ◽  
Vol 118 (46) ◽  
pp. e2100786118
Author(s):  
Jonas L. Juul ◽  
Johan Ugander
Keyword(s):  
Structural Properties ◽  
Information Diffusion ◽  
Spreading Process ◽  
Information Spread ◽  
Structural Differences ◽  
Classical Models ◽  
Diffusion Mechanisms ◽  
Speed Of Propagation ◽  
Types Of Information ◽  
False News

Do some types of information spread faster, broader, or further than others? To understand how information diffusions differ, scholars compare structural properties of the paths taken by content as it spreads through a network, studying so-called cascades. Commonly studied cascade properties include the reach, depth, breadth, and speed of propagation. Drawing conclusions from statistical differences in these properties can be challenging, as many properties are dependent. In this work, we demonstrate the essentiality of controlling for cascade sizes when studying structural differences between collections of cascades. We first revisit two datasets from notable recent studies of online diffusion that reported content-specific differences in cascade topology: an exhaustive corpus of Twitter cascades for verified true- or false-news content by Vosoughi et al. [S. Vosoughi, D. Roy, S. Aral. Science 359, 1146–1151 (2018)] and a comparison of Twitter cascades of videos, pictures, news, and petitions by Goel et al. [S. Goel, A. Anderson, J. Hofman, D. J. Watts. Manage. Sci. 62, 180–196 (2016)]. Using methods that control for joint cascade statistics, we find that for false- and true-news cascades, the reported structural differences can almost entirely be explained by false-news cascades being larger. For videos, images, news, and petitions, structural differences persist when controlling for size. Studying classical models of diffusion, we then give conditions under which differences in structural properties under different models do or do not reduce to differences in size. Our findings are consistent with the mechanisms underlying true- and false-news diffusion being quite similar, differing primarily in the basic infectiousness of their spreading process.

Are We Still Needed? Reflections on the Profession in BIALL's Fiftieth Anniversary Year

2019 ◽  
Vol 19 (02) ◽  
pp. 75-79 ◽  
Author(s):  
Dunstan Speight
Keyword(s):  
Information Service ◽  
Fiftieth Anniversary ◽  
Law Firm ◽  
Legal Information ◽  
Short Overview ◽  
Core Skills ◽  
Challenges And Opportunities ◽  
Types Of Information ◽  
Changing World

AbstractIn this article Dunstan Speight, President of BIALL 2018–2019, provides a short overview of current challenges and opportunities facing the profession. In addition to trends affecting all types of law libraries, the article discusses some of the main issues facing the three main types of information service: academic, law firm and chambers, and professional bodies. The article concludes with a discussion of how core skills and experience are still relevant in the fast-changing world of legal information.

scholarly journals Final Publication of the “Regulations on the Supervision and Administration of Cosmetics” and New Prospectives of Cosmetic Science in China

Cosmetics ◽  
2020 ◽  
Vol 7 (4) ◽  
pp. 98
Author(s):  
Zhe Su ◽  
Fei-ya Luo ◽  
Xin-rong Pei ◽  
Feng-lan Zhang ◽  
Shu-xia Xing ◽  
...  
Keyword(s):  
Research Work ◽  
Safety Evaluation ◽  
Regulatory System ◽  
Regulatory Requirements ◽  
Scientific Investigations ◽  
Scientific Research Work ◽  
Challenges And Opportunities ◽  
Technical Evaluation ◽  
New Policies ◽  
Evaluation Work

In June 2020, the new “Regulations on the Supervision and Administration of Cosmetics” (CSAR) was finally issued and published in China. This is the first revision of the “Regulations on Hygiene Supervision of Cosmetics” (CHSR) since its publication in 1989. As the basic and fundamental legislation for cosmetics, CSAR has a far-reaching impact on the whole industry and also reveals new trends in scientific research work. To provide an interpretation of this regulation and help enterprises and researchers better understand the new policies, in this study, the main contents of CSAR and its regulatory system were introduced, and the major changes and background considerations were summarized, especially in the definition and scope of cosmetics, classification and categorization, ingredient management, safety evaluation, efficacy substantiation and technical evaluation work. A brief review of technical progress worldwide and a comparison of regulatory requirements were provided where necessary. Finally, new prospects of cosmetic science in China were discussed. In conclusion, CSAR will initiate a renewed and integrated regulatory system for cosmetics. Advanced concepts of supervision, encouragement of innovation, utilization of technical approaches and emphasis on scientific investigations are reflected in the regulations, which will deeply influence the development of both cosmetic products and new ingredients. With all these new challenges and opportunities, everyone involved should get prepared.

scholarly journals A Comparative Study of Transactional and Semantic Approaches for Predicting Cascades on Twitter

2018 ◽  
Author(s):  
Yunwei Zhao ◽  
Can Wang ◽  
Chi-Hung Chi ◽  
Kwok-Yan Lam ◽  
Sen Wang
Keyword(s):  
Comparative Study ◽  
Information Diffusion ◽  
Large Scale ◽  
Semantic Features ◽  
Information Cascades ◽  
Social Media Data ◽  
Twitter Data ◽  
Pros And Cons ◽  
Media Data ◽  
Transactional Models

The availability of massive social media data has enabled the prediction of people’s future behavioral trends at an unprecedented large scale. Information cascades study on Twitter has been an integral part of behavior analysis. A number of methods based on the transactional features (such as keyword frequency) and the semantic features (such as sentiment) have been proposed to predict the future cascading trends. However, an in-depth understanding of the pros and cons of semantic and transactional models is lacking. This paper conducts a comparative study of both approaches in predicting information diffusion with three mechanisms: retweet cascade, url cascade, and hashtag cascade. Experiments on Twitter data show that the semantic model outperforms the transactional model, if the exterior pattern is less directly observable (i.e. hashtag cascade). When it becomes more directly observable (i.e. retweet and url cascades), the semantic method yet delivers approximate accuracy (i.e. url cascade) or even worse accuracy (i.e. retweet cascade). Further, we demonstrate that the transactional and semantic models are not independent, and the performance gets greatly enhanced when combining both.

scholarly journals Online Education during Covid-19: A Safe and Effective Way of Learning Research Techniques from a Mentor

2021 ◽  
Vol 11 (2) ◽  
pp. 06-14
Author(s):  
Ameer Ali ◽  
Maya Khemlani David
Keyword(s):  
Online Education ◽  
Research Work ◽  
Social Mechanisms ◽  
Pedagogical Tools ◽  
Microsoft Word ◽  
Online Platforms ◽  
Research Techniques ◽  
Challenges And Opportunities ◽  
Teachers And Students ◽  
Experiential Research

The Covid-19 pandemic has changed social mechanisms of our world causing many countries to impose either partial or complete lockdowns. Consequently, many people have resorted to online platforms for undertaking their daily business activities and jobs. Similarly, there is also an increasing trend of online education followed by both teachers and students around the world. Therefore, the aim of this research paper is to explore how a mentee learnt research techniques from a mentor through online platforms. Although researchers have studied the challenges and opportunities of online education during the pandemic, this research will explore how the mentee learnt research techniques from the mentor through emails, WhatsApp interaction, and Microsoft Word track changes feature. In this paper, we have used experiential research methodology for carrying out research. Employing qualitative method of data analysis, we have found out that the feedback and suggestions provided by a mentor to a mentee’s research work through the online platforms have been very safe and effective in improving the mentee’s research skills. Moreover, purposively selected chunks from the mentee’s six revised drafts have been discussed to demonstrate how online education facilitates practical learning during the pandemic. Finally, we are of the view that online platforms may be used as effective pedagogical tools because these facilitate learners to read their mentor’s feedback and suggestions as many times as they desire to improve their performance.

scholarly journals Instructing usability evaluation in LIS curriculum: A case of the U.S.

2011 ◽  
Vol 12 ◽  
pp. 1-7
Author(s):  
Kanwal Ameen ◽  
Sanda Erdelez
Keyword(s):  
Usability Evaluation ◽  
Information Services ◽  
Digital Information ◽  
Professional Career ◽  
Content Analysis Method ◽  
Other Information ◽  
Challenges And Opportunities ◽  
Accredited Schools ◽  
User Friendly ◽  
The U.S

Increasing use of websites as vehicles for the dissemination of information services in the digital environment and interaction with users has raised many usability concerns in creating user-friendly digital information services. Hence, it is important to understand if and how the future generations of library and other information professionals learn about usability evaluation through their LIS studies. Guided by this research objective, the authors of this paper reviewed the state of usability evaluation (UE) courses in LIS education. The study used content-analysis method to find answers to the research questions. The sample was purposive consisting only ALA accredited schools in the U.S. Publicly available descriptions of the courses on their websites were accessed to review the UE content offered. The content of these identified course descriptions was downloaded and further analyzed in terms of its format and coverage. Besides, based on the experience of the second author, the paper provides insight into both challenges and opportunities that the instructors of usability evaluation courses face. Findings reveal that LIS education programs have not yet fully accepted UE of digital resources as a standard course in their educational repertory. The study suggests that a systematic exposure to UE can place LIS professionals in a better position to communicate with the information technology staff regarding the specific needs of the users and enhance their chances for a productive professional career.

scholarly journals Product Recommendation System: A Systematic Literature Review

2021 ◽  
Vol 9 (VII) ◽  
pp. 3330-3339
Author(s):  
Ketki Kinkar
Keyword(s):  
Literature Review ◽  
Performance Measures ◽  
Systematic Literature Review ◽  
Recommender System ◽  
Recommendation System ◽  
Consumer Preferences ◽  
Research Work ◽  
Product Recommendation ◽  
System A ◽  
Scientific Papers

In today's world, we find a wide variety of search options and we may have difficulty selecting what we really need. The recommendation System plays an important part in dealing with these problems. A recommender system is a framework that is a filtering system that filters the data with various algorithms and recommends the user with the most relevant data. Recommendation systems are productive customization mechanisms, often up-to-date and recommendations based on current consumer preferences. These systems have shown to be extremely helpful in different areas of e-commerce, education, movies, music, books, films, scientific papers, and various products. This paper reviews many approaches of recommendation techniques with their upsides and downsides and diverse performance measures. We have reviewed various articles, analyzed their technique and approach, major features of the algorithm utilized, and potential areas for improvement in that research work.

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