177,308 research outputs found

    Extracting significant signal of news consumption from social networks: the case of Twitter in Italian political elections

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    According to the Eurobarometer report about EU media use of May 2018, the number of European citizens who consult on-line social networks for accessing information is considerably increasing. In this work we analyse approximately 106 tweets exchanged during the last Italian elections held on March 4, 2018. Using an entropy-based null model discounting the activity of the users, we first identify potential political alliances within the group of verified accounts: if two verified users are retweeted more than expected by the non-verified ones, they are likely to be related. Then, we derive the users’ affiliation to a coalition measuring the polarisation of unverified accounts. Finally, we study the bipartite directed representation of the tweets and retweets network, in which tweets and users are collected on the two layers. Users with the highest out-degree identify the most popular ones, whereas highest out-degree posts are the most “viral”. We identify significant content spreaders with a procedure that allows to statistically validate the connections that cannot be explained by users’ tweeting activity and posts’ virality, using an entropy-based null model as benchmark. The analysis of the directed network of validated retweets reveals signals of the alliances formed after the elections, highlighting commonalities of interests before the event of the national elections

    Communities, knowledge creation, and information diffusion

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    NOTICE: this is the pre-print version of a work deposited in arXiv (arXiv:0909.2481v1 [physics.soc-ph]) and submitted to the Journal of Informetrics. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in JOURNAL OF INFORMETRICS, [VOL 3, ISSUE 3, (2009)] DOI 10.1016/j.joi.2009.03.00

    Appropriate Similarity Measures for Author Cocitation Analysis

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    We provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis

    "Closing the R&D Gap, Evaluating the Sources of R&D Spending"

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    Both spending and tax policies have been implemented in the United States with the goal of stimulating private sector research and development (R&D). Karier questions whether current R&D policy, especially the research and experimentation tax credit, can contribute to closing the gap between nondefense expenditures on R&D in the United States and such expenditures in other countries, such as Japan and Germany. He also explores possible changes to our current R&D policy to make it more effective.

    Going Beyond Counting First Authors in Author Co-citation Analysis

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    The present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed

    Letter from R. R. Zellick, Assistant Trust Officer, Anglo California National Bank of San Francisco, to Joseph R. Goodman, October 2, 1942

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    Letter from R. R. Zellick, Assistant Trust Officer at The Anglo California National Bank of San Francisco, to Joseph R. Goodman, regarding property owned by Dave Tatsuno. Zellick mentions a dispute between current tenants and Tatsuno, and that Tatsuno has asked Goodman to help locate trustworthy tenants.Personal correspondence, organizational records, government documents, publications, and other papers created or collected by Joseph R. Goodman documenting the forced removal and incarceration of Japanese Americans during World War II, as well as organized resistance to incarceration. Included in the collection are records of the Japanese Young Men's Christian Association and the Japanese American Citizens' League in San Francisco, including papers of the Japanese YMCA's executive secretary Lincoln Kanai; Sakai family papers; Goodman's correspondence to and from Japanese American incarcerees, organizations opposing forced removal and incarceration of Japanese Americans, the War Relocation Authority, and others; publications, photographs, and ephemera from the Topaz Relocation Center, where Goodman taught high school; War Relocation Authority records and publications; and newspaper clippings, pamphlets, and reports about forced removal and incarceration created by various government, religious, and civic organizations, in California and nationwide

    Dispelling the Myths Behind First-author Citation Counts

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    We conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more sophisticated methods

    Self-citations, co-authorships and keywords: A new approach to scientists' field mobility?

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    peer reviewedThis paper introduces a new approach to detecting scientists' field mobility by focusing on an author's self-citation network, and the co-authorships and keywords in self-citing articles. Contrary to much previous literature on self-citations, we will show that author's self-citation patterns reveal important information on the development and emergence of new research topics over time. More specifically, we will discuss self-citations as a means to detect scientists' field mobility. We introduce a network based definition of field mobility, using the Optimal Percolation Method (Lambiotte & Ausloos, 2005; 2006). The results of the study can be extended to selfcitation networks of groups of authors and, generally also for other types of networks
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