The simple regularities in the dynamics of online news impact

Online news can quickly reach and affect millions of people, yet we do not know yet whether there exist potential dynamical regularities that govern their impact on the public. We use data from two major news outlets, BBC and New York Times, where the number of user comments can be used as a proxy of news impact. We find that the impact dynamics of online news articles does not exhibit popularity patterns found in many other social and information systems. In particular, we find that a simple exponential distribution yields a better fit to the empirical news impact distributions than a power-law distribution. This observation is explained by the lack or limited influence of the otherwise omnipresent rich-get-richer mechanism in the analyzed data. The temporal dynamics of the news impact exhibits a universal exponential decay which allows us to collapse individual news trajectories into an elementary single curve. We also show how daily variations of user activity directly influence the dynamics of the article impact. Our findings challenge the universal applicability of popularity dynamics patterns found in other social contexts.

Evolutionary Prediction of Nonstationary Event Popularity Dynamics of Weibo Social Network Using Time-Series Characteristics

A growing number of web users around the world have started to post their opinions on social media platforms and offer them for share. Building a highly scalable evolution prediction model by means of evolution trend volatility plays a significant role in the operations of enterprise marketing, public opinion supervision, personalized recommendation, and so forth. However, the historical patterns cannot cover the systematical time-series dynamic and volatility features in the prediction problems of a social network. This paper aims to investigate the popularity prediction problem from a time-series perspective utilizing dynamic linear models. First, the stationary and nonstationary time series of Weibo hot events are detected and transformed into time-dependent variables. Second, a systematic general popularity prediction model N- SEP 2 M is proposed to recognize and predict the nonstationary event propagation of a hot event on the Weibo social network. Third, the explanatory compensation variable social intensity (SI) is introduced to optimize the model N- SEP 2 M. Experiments on three Weibo hot events with different subject classifications show that our prediction approach is effective for the propagation of hot events with burst traffic.

Can we ‘feel’ the temperature of knowledge? Modelling scientific popularity dynamics via thermodynamics

Just like everything in nature, scientific topics flourish and perish. While existing literature well captures article’s life-cycle via citation patterns, little is known about how scientific popularity and impact evolves for a specific topic. It would be most intuitive if we could ‘feel’ topic’s activity just as we perceive the weather by temperature. Here, we conceive knowledge temperature to quantify topic overall popularity and impact through citation network dynamics. Knowledge temperature includes 2 parts. One part depicts lasting impact by assessing knowledge accumulation with an analogy between topic evolution and isobaric expansion. The other part gauges temporal changes in knowledge structure, an embodiment of short-term popularity, through the rate of entropy change with internal energy, 2 thermodynamic variables approximated via node degree and edge number. Our analysis of representative topics with size ranging from 1000 to over 30000 articles reveals that the key to flourishing is topics’ ability in accumulating useful information for future knowledge generation. Topics particularly experience temperature surges when their knowledge structure is altered by influential articles. The spike is especially obvious when there appears a single non-trivial novel research focus or merging in topic structure. Overall, knowledge temperature manifests topics’ distinct evolutionary cycles.

The key vectors of implementation of public initiatives in the area of extracurricular education of children in Eastern Siberia in the last quarter of the XIX – early XX centuries

This article is dedicated to examination of public participation in the formation and development of extracurricular education of children in Eastern Siberia. The relevance of this research is substantiated by the importance of public sociocultural initiatives in modern Russia. The author highlights the key vectors of public innovation sociocultural activity, which included environmental education, organization of reading events and libraries for children, staging of performances, literary and musical mornings, physical education and play activities. Within the framework of these directions, the author determines their popularity, dynamics and interpretation of goals by the actors of sociocultural activity. Extracurricular education was intended for all population groups, and opened new dimensions for social interaction not only for children, but for parents as well. The research is based on the comparative methodology, and methodological ideas of V. A. Glazychev on the interpretation of city as a sociocultural phenomenon and the ability of urban community to create and maintain the conditions for its development through the efforts of all residents with the leading role of mobile innovation minority. In Eastern Siberia, the development of extracurricular educational work generally corresponded with the nationwide, but at a slower pace and smaller scale. The conclusion is made that in the provincial cities, the intelligentsia led moderate, although considerable activity on the development of applied problems of pedagogy, orienting towards the needs of a child. Overall, innovation social activity expanded the “geography of childhood” of the children involved. The public initiative filled the gap in the state system of extracurricular education and evolved to the creation of multifunctional recreation and educational centers for children.

Stretched Exponential Dynamics in Online Article Views

Article view statistics offers a measure to quantify scientific and public impact of online published articles. Popularity of a paper in online community changes with time. To understand popularity dynamics of article views, we propose a decay dynamics based on a stretched exponential model. We find that a stretched exponent gradually decreases with time after online publication following a power-law scaling. Compared with a simple exponential or biexponential model, a stretched exponential model with a time-dependent exponent well describes long-tailed popularity dynamics of online articles. This result gives a useful insight into how popularity diminishes with time in online community.

Popularity Dynamics of Social and Affordable Housing: Ethics vs Business

This paper summarizes the arguments and counterarguments within the scientific discussion on the issue of social housing, existing ethical dilemmas, and business development. The main purpose of the research is to investigate the interest level and popularity dynamics of social and affordable housing in the world in general and in OECD countries. The systematization of literary sources and approaches for solving the problem of ethical and economical aspects of social and affordable housing indicates that there is no single point of view on this issue among scientists. That is why the essence of the concepts of social, affordable, and public housing needs to be clarified considering existing differences. Besides it, comparative analysis of the results of analytical analysis of the interest level and popularity dynamics of social and affordable housing based on Google Trends tools and the results of statistical analysis in this context has not been conducted yet. Investigation of the topic about popularity dynamics of social and affordable housing emphasizing ethical needs and expected business benefits in the paper is carried out in the following logical sequence: systematization and clarification theoretical approaches to determine the essence and the difference between social, public and affordable housing; description of dominant types of funding social and affordable housing; analytical analysis of popularity dynamics of social and affordable housing with the determination of key value picks; statistical analysis of certain social housing indicators; comparing the results and making conclusions. Methodological tools of the research methods were logical generalization and scientific abstraction, statistical and structural analysis, comparative, and graphical analysis using the Excel software. Analytical analysis was realized based on Google Trends tools. The objects of research were the search requests about social, public, and affordable housing in the world in 2004-2021, and the indicators of social housing from the sample of OECD countries and other EU countries (limit in 2018 due to the availability of information on open information portals of The Organization for Economic Co-operation and Development). The paper presents the results of analytical, statistical, and comparative analysis of the level of interest (popularity) and development of social and affordable housing. The recommendations according to the coexistence of ethical and entrepreneurial principles can be useful for public and private investors in social and affordable housing.

Understanding Time-Evolving Citation Dynamics across Fields of Sciences

Scholarly publications draw collective attention beyond disciplines, leading to highly skewed citation distributions in sciences. Uncovering the mechanisms of such disparate popularity is very challenging, since a wide spectrum of research fields are not only interacting and influencing one another but also time-evolving. Accordingly, this study aims to understand citation dynamics across STEM fields in terms of latent affinity and novelty decay, which is based upon Bayesian inference and learning of the Affinity Poisson Process model (APP) with bibliography data from the Web of Science database. The approaches shown in the study can shed light on predicting and interpreting popularity dynamics in diverse application domains, by considering the effect of time-varying subgroup interactions on diffusion processes.