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The advancement in computing and communication technologies permits folks to induce along and share data in innovative ways that. Social networking sites (a recent phenomenon) empower folks of various ages and backgrounds with new kinds of collaboration, communication, and collective intelligence. Prodigious numbers of on-line volunteers collaboratively write book of facts articles of unexampled scope and scale; on-line marketplaces suggest merchandise by investigation user searching behaviour and interactions; and political movements conjointly exploit new kinds of engagement and collective action. within the same method, social media give sample opportunities to check human interactions Associate in Nursingd collective behaviour on an unexampled scale.

'Collective behavior' theory has its roots in antidemocratic theorists of 19th cent Europe, esp G. LeBon (THE CROWD, New York, NY: Viking Press, 1960). US sociol'ts have modified but not eliminated these biases, particularly the imputation of 'irrationality' to collective action. Yet evidence sugsuggests that rioters, for instance, are more 'rational' than is often supposed, & that authorities are also capable of 'irrationality.' This paper critically examines N. Smelser's signif efforts to organize the field systematically (THEORY OF COL- LECTIVE BEHAVIOR, New York, NY: Free Press, 1962). It is argued that Smelser's efforts result in a 'systematization' that often confounds rather than clarifies; that his conceptual org is founded on undemonstrated assertions about the 'exaggerated' character of 'uninstit'ized' beliefs & behavior; that his values are unstated or unclear; & that, whatever his values, he tends to drift into a managerial or admin'ive vision of collective action. (See also SA 0829/E9781.) HA.

This article reviews the study of mass behavior (known as collective behavior in America) in Germany. The historical scope of this review is approximately one hundred years beginning with a discussion of the works of Marx, Weber, Tönnies and Simmel. This discussion is followed by an analysis of how the study of mass behavior dealt with the rise and aftermatch of National Socialism. Finally the collective behavior research which has been done in the post war period is reviewed ending with a brief description of the work being done in the subspeciality of the Sociology of Disasters.

"Collective behavior" theory has its roots in antidemocratic theorists of nineteenth century Europe, espe cially LeBon. American sociologists have modified but not eliminated these biases, particularly the imputation of "irra tionality" to collective action. Yet evidence suggests that rioters, for instance, are more "rational" than is often sup posed, and that authorities are also capable of "irrationality." In this paper, we critically examine Smelser's significant efforts to organize the field systematically. We argue that Smelser's efforts result in a "systematization" that often confounds rather than clarifies; that his conceptual organization is founded on undemonstrated assertions about the "exaggerated" character of "uninstitutionalized" beliefs and behavior; that his values are unstated or unclear; and that, whatever his values, he tends to drift into a managerial or administrative vision of collective action.

The unit of analysis used by D. Jaros & M. A. Baer ("Political Disaffection in the American States: Substantive and Symbolic Policy Determinants," Social Science Quarterly, 1976, 57, Dec, 592-598) in their examination of the relationship between the output of state policy & collective behavior was the state, & therefore it is not surprising that they found a relationship. Generally, the larger the unit of analysis, the greater the likelihood of stronger statistical relationships. With the introduction of controls into Jaros's & Baer's data set, significant correlations disappear. In a reply entitled Disaffection for 'State Policy Outputs and Collective Behavior', Jaros & Baer (U of Kentucky) contend that I. Wasserman offered an unproductive critique of their work, because: (1) he uses indice segments originally constructed to operationalize certain concepts, (2) he computationally transforms some of these segments, & (3) he does not use multiple correlations as did the original data, thereby distorting any comparison. Wasserman's omissions & errors in data presentation impair the quality of his critique. For example, he fails to mention the Carnegie Commission's classification procedure for "research institutions," & information on other classification criteria, such as that for a liberal arts Coll, is false. Hopefully efforts at criticism will improve to benefit authors & the profession. L. Kamel.

AbstractWe provide a detailed study of the threshold model, where both conformist and anti-conformist agents coexist. Our study bears essentially on the convergence of the opinion dynamics in the society of agents, i.e., finding absorbing classes, cycles, etc. Also, we are interested in the existence of cascade effects, as this may constitute an undesirable phenomenon in collective behavior. We divide our study into two parts. In the first one, we basically study the threshold model supposing a fixed complete network, where every one is connected to every one, like in the seminal work of Granovetter. We study the case of a uniform distribution of the threshold, of a Gaussian distribution, and finally give a result for arbitrary distributions, supposing there is one type of anti-conformist. In a second part, we suppose that the neighborhood of an agent is random, drawn at each time step from a distribution. We distinguish the case where the degree (number of links) of an agent is fixed, and where there is an arbitrary degree distribution. We show the existence of cascades and that for most societies, the opinion converges to a chaotic situation.

It is suggested that most researchers organize the field of collective behavior & social movement along productive principles that must compete with each other & the oft-neglected tasks of organizing & cumulating research findings. Six competing principles are outlined & contrasted with the goal of systematizing research data: the trash & icon, perspectives, themes, popular categories, area studies, & the movement assistance principles. Additionally, four strategic decisions (unit, aspects, generic questions, propositional answers) & six operational decisions (inclusion criteria, processing methods, propositional emphasis, documentary text, inventory & synthesis, causal logic) decisions faced by researchers who are attempting to organize & cumulate research data are examined. 75 References. Adapted from the source document.