Hotel Value Dimensions and Tourists' Perception of the City. The Case of St. Petersburg
In this work in progress, we analyze how perceived hotel value dimensions and the perception of city sights are connected with categories of hotels. Applying a topic modelling algorithm to 21,165 reviews from 201 hotels located in Saint Petersburg, we show that clients of hotels of different categories pay attention to different value dimensions. Analyzing local aspect of value perception, we show how existing differences in perceiving the city by guests of the hotels can be explained in terms of the diversity of the socioeconomic status of clients.
This book provides an in-depth comparative analysis of inequality and the stratification of the digital sphere.
Grounded in classical sociological theories of inequality, as well as empirical evidence, this book defines ‘the digital divide’ as the unequal access and utility of internet communications technologies and explores how it has the potential to replicate existing social inequalities, as well as create new forms of stratification. The Digital Divide examines how various demographic and socio-economic factors including income, education, age and gender, as well as infrastructure, products and services affect how the internet is used and accessed. Comprised of six parts, the first section examines theories of the digital divide, and then looks in turn at:Highly developed nations and regions (including the USA, the EU and Japan); Emerging large powers (Brazil, China, India, Russia); Eastern European countries (Estonia, Romania, Serbia); Arab and Middle Eastern nations (Egypt, Iran, Israel); Under-studied areas (East and Central Asia, Latin America, and sub-Saharan Africa).
Providing an interwoven analysis of the international inequalities in internet usage and access, this important work offers a comprehensive approach to studying the digital divide around the globe. It is an important resource for academic and students in sociology, social policy, communication studies, media studies and all those interested in the questions and issues around social inequality.
This article addresses the questions, What do children in urban areas do on Saturdays? What type of organizational resources do they have access to? Does this vary by social class? Using diary data on children’s activities on Saturdays in the Phoenix-Mesa-Scottsdale metropolitan area, the authors describe the different types of venues (households, businesses, public space, associations, charities, congregations, and government/tribal agencies) that served different types of children. They find that the likelihood of using a charity or business rather than a government or tribal provider increased with family income. Also, the likelihood of using a congregation or a government facility rather than business, charity, or household increased with being Hispanic. The authors discuss implications for the urban division of labor on Saturdays and offer research questions that need further investigation.
The goal of the conference is to help build cross-disciplinary networks of analysts, software specialists, and researchers to advance the use of textual information in multiple science, technology, and business development fields. Within this context, conference themes will include, but are not limited to:
DataSourcing, preparing, and interpreting data sources including patents, publications, webscraping, and other novel data sources
Text-mining tools and methodsBest practices in software-based topic modeling, clumping, association rules, term manipulation, text manipulation, etc. Visualization
Applied researchFuture-Oriented Technology Analysis (FTA) Intelligence gathering to support decision-making in the private sector (e.g., Management of Technology)
As a matter of great importance the information and communication technologies (ICT) development are searched in this paper. Indicators using for measuring and fostering progress in this area are widely used in ranking countries last decade. But the development of the country’s regions needs attention as well; especially it concerns such a large country as Russia. The heterogeneity of its regional structure is shown. As an classification criterion the innovative development is proposed. Using advanced statistical parametrical and non-parametrical methods allows defining the stratification of regions. The level of ICT development in groups (strata) of regions has been compared.
An important text mining problem is to find, in a large collection of texts, documents related to specic topics and then discern further structure among the found texts. This problem is especially important for social sciences, where the purpose is to nd the most representative documents for subsequent qualitative interpretation. To solve this problem, we propose an interval semi-supervised LDA approach, in which certain predened sets of keywords (that dene the topics researchers are interested in) are restricted to specic intervals of topic assignments. We present a case study on a Russian LiveJournal dataset aimed at ethnicity discourse analysis.
An important text mining problem is to find, in a large collection of texts, documents related to specific topics and then discern further structure among the found texts. This problem is especially important for social sciences, where the purpose is to find the most representative documents for subsequent qualitative interpretation. To solve this problem, we propose an interval semi-supervised LDA approach, in which certain predefined sets of keywords (that define the topics researchers are interested in) are restricted to specific intervals of topic assignments.
In this paper we introduce a generalized learning algorithm for probabilistic topic models (PTM). Many known and new algorithms for PLSA, LDA, and SWB models can be obtained as its special cases by choosing a subset of the following “options”: regularization, sampling, update frequency, sparsing and robustness. We show that a robust topic model, which distinguishes specific, background and topic terms, doesn’t need Dirichlet regularization and provides controllably sparse solution.
The purpose of this research is to describe the agenda set by the Internet-active part of the Russian public in Russia’s leading blog platform LiveJournal. This is done through modelling the Livejournal’s topic structure viewed as a reflection of online public opinion. Topic modelling is performed automatically with a LDA algorithm, and complemented with hand labelling of topics. Data are collected by the original software to a relational database that houses all posts of Livejournal top users from three selected periods. The research finds that Livejournal top users share their attention evenly between social / political and private / recreational issues, the latter being very stable, while the influence of protests in 2011 is clearly visible in the political part of the blogs’ content. The group of topics centred around social issues demonstrates the biggest volatility and may serve as an online public opinion barometer that may be applied for proactive policy making.