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By sociology Pareto means a synthesis of all the particular researches and disciplines dealing with human society—law, economics, political history, the history of religion, and so on—in a search for the relationships between social facts (1, 2). Sociology is to provide a framework into which will fit the results of these specialized studies; it is to be a comprehensive study which aims at discovering the principles underlying the form and changes of society in general.Such is Pareto's own formulation. It is apparent that he believes both that there are general principles underlying the form and changes of society, and that these can be discovered by a new discipline, sociology, working on the results of the specialized studies. The primary concern of the new discipline must therefore be methodology, and Pareto devotes much more attention to the problem of method in the social sciences than he does to the construction of his own theory of society. His justification for this is his belief that the methods of all previous sociologists have been basically faulty and can lead only to invalid conclusions. In this paper it is proposed to follow Pareto's emphasis, and to deal with his analysis of social facts and his general theory of society primarily with a view to bringing out those aspects which raise the problem of method in the social sciences.

Social sciences have gone too far in their specialization; their highly sophisticated methodological input is bringing diminishing returns in understanding the complexities & development trends of modern societies. More thought should be devoted to an integrated social science approach & to further elaboration of the broad-ranging theories of earlier times. In order not to fall victim to an orientation dilemma, ie, where one knows too much about too little, or too little about too much, a strategy of four-fold balance is delineated: balance in focus, in proportionality, in conceptualization, & in method. Modified AA.

The integration of social science with computer science and engineering fields has produced a new area of study: computational social science. This field applies computational methods to novel sources of digital data such as social media, administrative records, and historical archives to develop theories of human behavior. We review the evolution of this field within sociology via bibliometric analysis and in-depth analysis of the following subfields where this new work is appearing most rapidly: ( a) social network analysis and group formation; ( b) collective behavior and political sociology; ( c) the sociology of knowledge; ( d) cultural sociology, social psychology, and emotions; ( e) the production of culture; ( f) economic sociology and organizations; and ( g) demography and population studies. Our review reveals that sociologists are not only at the center of cutting-edge research that addresses longstanding questions about human behavior but also developing new lines of inquiry about digital spaces as well. We conclude by discussing challenging new obstacles in the field, calling for increased attention to sociological theory, and identifying new areas where computational social science might be further integrated into mainstream sociology.

Graphical representation of the dynamic interactions among the elements of a system has found wide application in business, government, & the "system sciences." Although system representation is now ad hoc, it may be possible to develop a standard theoretical presentation in terms of the interaction & feedback of biological, biosocial, cultural, & situational determinants of behavior. The resulting framework must, of course, be modified for each problem addressed, yet the framework forces the analysis to be dynamic as well as static, to avoid overemphasis on factors of interest to a particular investigator, & to show more precisely the effect of adopting alternative social theories. Examining the applicability of this proposed framework to a variety of problems suggests that this approach will assist in the transfer of information between applied & theoretical studies & in the cumulation of social science knowledge. 1 Table, 8 Figures. AA.

Instrumental variable (IV) methods provide a powerful but underutilized tool to address many common problems with observational sociological data. Key to their successful use is having IVs that are uncorrelated with an equation's disturbance and that are sufficiently strongly related to the problematic endogenous covariates. This review briefly defines IVs, summarizes their origins, and describes their use in multiple regression, simultaneous equation models, factor analysis, latent variable structural equation models, and limited dependent variable models. It defines and contrasts three methods of selecting IVs: auxiliary instrumental variable, model implied instrumental variable, and randomized instrumental variable. It provides overidentification tests and weak IV diagnostics as methods to evaluate the quality of IVs. I review the use of IVs in models that assume heterogeneous causal effects. Another section summarizes the use of IVs in contemporary sociological publications. The conclusion suggests ways to improve the use of IVs and suggests that there are many areas in which IVs could be profitably used in sociological research.