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      Democratic summary of public opinions in free-response surveys

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          Abstract

          Social surveys have been widely used as a method of obtaining public opinion. Sometimes it is more ideal to collect opinions by presenting questions in free-response formats than in multiple-choice formats. Despite their advantages, free-response questions are rarely used in practice because they usually require manual analysis. Therefore, classification of free-format texts can present a formidable task in large-scale surveys and can be influenced by the interpretations of analysts. In this study, we propose a network-based survey framework in which responses are automatically classified in a statistically principled manner. This can be achieved because in addition to the texts, similarities among responses are also assessed by each respondent. We demonstrate our approach using a poll on the 2016 US presidential election and a survey taken by graduates of a particular university. The proposed approach helps analysts interpret the underlying semantics of responses in large-scale surveys.

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          Objective Criteria for the Evaluation of Clustering Methods

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            Mapping Change in Large Networks

            Change is a fundamental ingredient of interaction patterns in biology, technology, the economy, and science itself: Interactions within and between organisms change; transportation patterns by air, land, and sea all change; the global financial flow changes; and the frontiers of scientific research change. Networks and clustering methods have become important tools to comprehend instances of these large-scale structures, but without methods to distinguish between real trends and noisy data, these approaches are not useful for studying how networks change. Only if we can assign significance to the partitioning of single networks can we distinguish meaningful structural changes from random fluctuations. Here we show that bootstrap resampling accompanied by significance clustering provides a solution to this problem. To connect changing structures with the changing function of networks, we highlight and summarize the significant structural changes with alluvial diagrams and realize de Solla Price's vision of mapping change in science: studying the citation pattern between about 7000 scientific journals over the past decade, we find that neuroscience has transformed from an interdisciplinary specialty to a mature and stand-alone discipline.
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              A Method of Automated Nonparametric Content Analysis for Social Science

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                Author and article information

                Journal
                09 July 2019
                Article
                1907.04359
                cdf4a64f-43b5-474c-a9eb-756a4d2fa67f

                http://arxiv.org/licenses/nonexclusive-distrib/1.0/

                History
                Custom metadata
                7 + 13 pages, 3 + 6 figures, 3 tables
                cs.SI physics.soc-ph

                Social & Information networks,General physics
                Social & Information networks, General physics

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