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Social Science Research, 1982
This paper seeks to discover whether the known inaccuracy of informant recall about their communication behavior can be accounted for by experimentally varying the time period over which recall takes place. The experiment took advantage of a new communications medium (computer conferencing) which enabled us to monitor automatically all the interactions involving a subset of the computer network. The experiment itself was administered entirely by the computer, which interviewed informants and recorded their responses. Variations in time period failed to account for much of the inaccuracy, which continues, as in previous experiments at an unacceptably high level. One positive finding did emerge: although the informants did not know with whom they communicated, the informants en masse seemed to know certain broad facts about the communication pattern. All other findings were negative. For example, it is impossible to predict the people an informant claimed to communicate with but did not; and it is impossible to predict who the five people are that an informant forgot to mention that she or he had communication with. Thus, despite their presumed good intentions, our tindings here confum what we have learned from six previous experiments: what people say about their communications bears no
Informant Accuracy in Social Network Data II
Human Communication Research, 1977
This paper repeats and confirms the results of Killworth and Bernard (1976), concerning informants' ability to report their communication accurately. A variety of selfmonitoring, or nearly self-monitoring, networks are used for this study. The conclusion again appears that people do not know, with any accuracy, those with whom they
… , Bled, Slovenia, September 24-26, 1992, 1993
In the paper the results of an experiment in measuring the effect of two alternative methods for collecting social network data are presented. Recall and recognition of the communication flow, identified between twelve members and advisers of the Student Government of the University in Ljubljana, were compared according to : • the size of egocentric networks and • the stability of naming. The hypotheses were : • the average size of the recalled egocentric network would be smaller than the recognized one and the differences would be minor, • the respondent with larger recalled network would have larger recognized network. All hypotheses were confirmed for one of the three defined relations. Difficulties with the two other relations could be explained by the two different content criteria included in the questions for identifying these two relations .
Journal of Communication and Computer（Issue 8，2013）
This paper reports the development of finite element software for creep damage analysis. Creep damage deformation and failure of high temperature structure is a serious problem for power generation and it is even more technically demanding under the current increasing demand of power and economic and sustainability pressure. This paper primarily consists of three parts: (1) the need and the justification of the development of in-house software; (2) the techniques in developing such software for creep damage analysis;
Computer Analysis of Texts in Social Networks, Its Method and Tools
Techno-Social Systems for Modern Economical and Governmental Infrastructures
Texts in virtual social networks differ cardinally from those of reviewed and edited publications, as being in fact the materials of non-moderated chat dialog having all the syntactic features, and in many cases, they are hypertexts with, as analysis subjects, quite relative boundaries. Instead of texts the virtual discourse, an object of new type is analyzed. In these conditions, the linguistic analysis is transformed into preliminary linguistic processing the texts and analysis of texts into the analysis of networks…
Analysis of Social Networks and Group Dynamics from Electronic Communication
Chapman & Hall/CRC Data Mining and Knowledge Discovery Series, 2008
The field of social network analysis evolved from the need to understand social relationship and interactions within a group of individuals. Knowing all individuals (employees) in an organization is difficult for an employee due to his/her limited bandwidth. Thus, in an organization's social network, not everyone directly knows (or interacts) with each other (Cross et al., 2002). Nor does an individual observe all the communication between individuals known (or unknown) to him/her directly. The result is that each individual forms perceptions about communication between other individuals, and uses them in his/her daily tasks. Having correct perceptions for all individuals in the organization is of utmost importance for the proper functioning of business processes. Cognitive analysis of social networks has grown out of this interest in understanding what an individual's perceptions are about other individuals in terms of who they know (socio-cognitive network analysis), or what knowledge they have (cognitive-knowledge network analysis) (Wasserman and Faust, 1994). Traditional cognitive analysis approaches depend on the use of surveys and feedback from individuals. However, the lack of inability to collect large datasets, as well as problems such as inherent bias in responses, makes it difficult to analyze such social networks on a large scale. The widespread adoption of computer networks in organizations and the use of electronic communication for business processes have fostered a new age in social network analysis. E-mail communication, for example, is widely used by employees to exchange information. An email server observes all such communication between individuals in the organization, and therefore can analyze the email logs to determine the perceived social network for each individual, as well as the gold standard (or ground truth or real) social network. Given the large dataset sizes, it is difficult to apply existing techniques, since they do not scale very well. Hence, new efficient, scalable techniques are required for the socio-cognitive network analysis. First, the problem of socio-cognitive analysis of a social network is presented. This is described using email communication network, and then our previous simple yet scalable approach is presented for such analysis. The approach can likewise be applied to other communications like instant messages. Previous case study using the proposed approaches on Enron email logs is then described. It uses the Enron email dataset, wherein the email communication between the employees of Enron is analyzed using the email logs before and after the Enron crisis of 2001. The second part of the paper describes the problem of modeling and analysis of group dynamics in a social network. Data logs from a multi-player network based game, Sony EverQuest2, are now available, and are part of our current research on group dynamics. A brief overview of this problem is described and current research directions are explained.