The article provides a brief review of social sequence analysis as an algorithmic deterministic approach to the classification of event series. The method is discussed in the context of its reception in social sciences in early 1980s with the help of a pioneering research enthusiast A. Abbott. The specificity of sociological applications of sequence analysis under certain data assumptions inherited from bioinformatics, e.g. universal interchangeability of events, arbitrary censoring, rank time variable, is considered. The article classifies a broad set of methods of time-ordered data analysis to provide a base for epistemological confrontment and pinpoint the advantages and shortcomings of sequence analysis compared to nonparametric statistics and general linear models of ordered events. The bases of classification are the dichotomies of time/order event definition and algorithm/ statistical inference method of result acquiring. The comparison covers different methods’ applications in cases of varied research goals, data types and theoretical assumptions. The article provides a sketch of sequence analysis development over time, considering its aggressive movements towards positioning on the bases of philosophy of history and narrative criticism of general linear models. The roots of its recent orientation towards visualization techniques are discussed as revealed in the scope of early 2000’s controversy over the capability of the use of sequence analysis to solve the theoretical problems stemming from the limitations of general linear models.
The paper is devoted to the procedures of automatic data extraction from web pages, i.e., web scraping of web data. We consider different types of web data such as digital traces and other numeric and text web data as well as its advantages (the speed of data collection and, as a consequence, the continuous coverage, efficiency, etc.) and limitations (the limited representativeness, difficulties in organizing storage of a large amount of data, deviation from the traditional procedure for setting up a study, etc.) in comparison with traditional methods of data collection. Various tools of web data extraction (API, requests, and selenium) are described to illustrate principles of handling static and dynamic web pages. The paper also gives an overview of the basic minimum of competencies for web scraping: in particular, programming using Python and navigating through the web pages’ code. A detailed illustration is given based on a fragment of the data collection process from a recent relevant Russian study.
настроения, эмоции, поведение, рабочие, кластерный анализ, классификация, типология
At first glance, biographical methods in sociology on the one hand and critical discourse analysis on the other hand occupy opposite positions on the structure-agency spectrum. While biographical sociology assumes great agency on the side of interviewees and examines an interview as text, critical discourse analysis focuses on texts produced in specific institutional frameworks. This paper examines the possibilities and limitations for combining these two approaches in a research project. First, the author juxtaposes the underlying assumptions of biographical research as done by Gabriele Rosenthal and the foundations of critical discourse analysis as done by Siegfried Jäger. Next, the author presents an example of an empirical situation where a combination of the approaches can be methodologically sound for a qualitative research project. The author thus offers a methodological argument for combining biographical sociology with critical discourse analysis, illustrating the merits of such a mixed approach with the example of a study on biographies of Russian-Germans and discourses which surround Russian-German policies in Germany.
Conducting online interview via video applications is becoming a widespread interview mode. Such programs as Skype, Google Hangouts etc may be useful for interviews with people from different countries.
The problem is whether two modes: technically mediated and face to face, can be used as equal in the same research. We suggest an analysis for all the types of technically-mediated interviews in order to suggest the criteria of similarity using comparative cases. The empirical research reveals the differences that may be detected in interviewing process and whether they influence the results.
The article reflects some potentially distorting circumstances and suggests how to avoid them.
The paper is addressed to an approach to working with a missing data "as is". I.e. it is supposed that missing data becomes one more category of the exploring variable. Such an approach to working with missings is radically different from alternative approaches: they are to delete those observations which contain missings or replace missings with valid data. The only method known to us which makes it possible to implement the approach of working with missings "as is" is CHAID. CHAID refers to the decision trees class of methods; in itself, this method is very interesting and relevant for researchers dealing with categorical variables and nonlinear associations.
In the literature, we did not find an answer to the question what are the advantages and limitations of the approach to working with missings "as is" implemented in CHAID comparing to the mentioned alternative approaches. Despite this, tree models with missing data are often found in empirical studies. To start a discussion considering this issue, we conducted several series of statistical experiments on generated data organized into three predictors of categorical and interval measure type. It was empirically established that, on the whole, the method correctly distributes missings in tree's nodes, but in most cases, the inclusion of missings in an analysis is accompanied by changes in tree's structure, and therefore there is a risk of obtaining incorrect, false, erroneous conclusions. The paper also provides recommendations on what factors should be considered when deciding whether to include missing in an analysis "as is".
While changing from one survey method to another, the role of the interviewer changes substantially, however, in current Russian studies this is not given proper consideration. Furthermore, the expectations of the interviewers about the transition to a new method of survey data collection may influence the success of this transition. One of the possible ways to change these expectations are the trainings that accompany the transition to a new method of data collection. In this paper we provide an ethnographic description of the actual and semantic component of the trainings for the interviewers of the RLMS–HSE on the transition from PAPI to CAPI. This description is supplemented by semi-formalized interviews with the field staff who conducted the trainings, and with the heads of the RLMS– HSE. After this, we tried to statistically reveal the effect of trainings on the interviewer's expectations.
This research aimed to develop of scale for measuring of attitude to opera and ballet theatre. Unlike existing research on aesthetic attitudes, this paper develops scale, measuring attitude to a theatre, but not to its repertoire. The paper considers fashion is the attitude’s dimension and proposes the set of indicators measuring fashion appear in the visitors’ attitude. This study extends existing knowledge about the attitude to high culture institution and answers the question about the effectiveness of the theatre’s marketing communications. Empirical data comes from two research projects consisting of in-depth interviews and surveys. Study 1 aimed to develop the scale based on in-depth interviews, Likert’s procedure, principal component analysis and confirmatory factor analysis. The goal of Study 2 was to evaluate the scale with a bigger sample and to check the scale’s validity. Confirmatory factor analysis reveals a two-dimensioned model of the disposition showing the good fit of the model to empirical data in both studies. The fashion dimension is statistically significant. As a result, a 13-item scale was developed and evaluated, showing the attitude to the theatre divided into two subscales. The first one reflects theatre as a source of personal development, exciting and knowledge. The second one displays the attitude to the theatre’s popularity. The directions of further work are discussed.
The review article covers some conceptualizations and methodological approaches to distributive justice research in social sciences. It analyses terminology issues, differences in research programs, and the following methodological issues. The article looks into the issues of applying the term ‘justice’ for varying phenomena and different terms such as ‘justice’, ‘fairness’ and ‘equity’ for the same phenomenon. The author considers some possible sources of conceptual ambiguity along with the main differences between the discussed conceptions of distributive justice. The most significant directions of distributive justice research are critically revised. Considering the different views on social norms among theoretical approaches, these assumptions are highlighted for further classification of methods inside the distributive justice research field. The author introduces some methodological distinctions, including research’s divergent aims and subjects, as well as data collection methods. The article proposes the classification of methods considering the inner connections between the distributive justice conceptions and the methodological approaches. The division of labor in the research field of distributive justice is depicted. The proposed classification might be helpful for choosing the proper research methods and for the conceptual clarification in the specific empirical studies.