1,720,962 research outputs found
Open dataset of scholars on Twitter (X)
No full text<p>This is a version 2 dataset of paired OpenAlex author IDs (<a href="https://docs.openalex.org/about-the-data/author">https://docs.openalex.org/about-the-data/author</a>) and Twitter (now X) user IDs<br><br></p>
<p><strong>Major update in this version</strong></p>
<p>Following the significant update to OpenAlex's author identification system, the scholars on Twitter dataset, which previously linked Twitter IDs to OpenAlex author IDs, immediately became outdated. This called for a new approach to re-establish these links, as the absence of new Twitter data made it impossible to replicate the original method of matching Twitter profiles with scholarly authors. To navigate this challenge, a bridge was constructed between the June 2022 snapshot of the OpenAlex database—used in the original matching process—and the most recent snapshot from February 2024. This bridge utilized OpenAlex works IDs and DOIs to match authors in both datasets by their shared publications and identical primary names. When a connection was established between two authors with the same name, the new OpenAlex author ID was assigned to the corresponding Twitter ID. When direct matches based on primary names were not found, an attempt was made to establish connections by matching the names from June 2022 with any corresponding alternative names found in the 2024 dataset. This method ensured continuity of identity through the system update, adapting the strategy to link profiles across the temporal divide created by the database's overhaul.</p>
<p>Our efficient method for re-establishing links between author IDs and Twitter profiles has been notably successful, managing to rematch 432,417 (88%) OpenAlex author IDs. This effort successfully restored connections for 388,968 unique Twitter users, which represents 92% of the original dataset. Of these, 375,316 were matched using their primary names, and 57,101 through alternative names. The simplicity and quick execution of this approach led to exceptionally favourable results, with a minimal loss of only 8% of the original Twitter-linked scholarly accounts.</p>
<p>The dataset includes <strong> 432,417 unique author_ids</strong> and <strong>388,968 unique tweeter_ids</strong> forming <strong>462,427 unique author-tweeter pairs</strong>.</p>
<p> </p>
<p><strong>File descriptions</strong></p>
<ul>
<li><strong>authors_tweeters_2024_02.csv</strong> is the actual dataset of author IDs paired with tweeter IDs. The "alternative" column indicates if the match was made with the primary name (0) or an alternate name (1).</li>
<li><strong>mapping_tweeters_2022_2024.csv</strong> contains the relationship made between the 2022 author IDs and the 2024 author IDs, including the names.</li>
</ul>
<p> </p>
<p><strong>How to cite</strong></p>
<p>When using the dataset, please cite the following article providing details about the matching process:</p>
<div>
<div>Mongeon, P., Bowman, T. D., & Costas, R. (2023). An open data set of scholars on Twitter. <em>Quantitative Science Studies</em>, 1–11.
<div><a href="https://doi.org/10.1162/qss_a_00250">https://doi.org/10.1162/qss_a_00250</a></div>
</div>
</div>
Open dataset of scholars on Twitter
No full textIMPORTANT NOTE: This dataset was created using the May 2022 OpenAlex data dump. In June 2023, OpenAlex announced the implementation of a new author disambiguation algorithm that replaced all the old IDs with new ones, essentially making the dataset unusable. A new version of the dataset using the new OpenAlex author IDs is being prepared and will be available shortly.
This is a dataset of paired OpenAlex author_ids (https://docs.openalex.org/about-the-data/author) and tweeter_ids (usernames).
The dataset includes 492,124 unique author_ids and 423,920 unique tweeter_ids forming 498,672 unique author-tweeter pairs. The file contains the following columns:
Column
Description
author_id
author_id from OpenAlex
tweeter_id
tweeter_id of the Twitter user
criteria
A list of the different matching criteria that identified the pair
valid
This column indicates whether the match has been manually checked. A 0 indicates a false positive, and a 1 indicates a true positive. Empty rows have not been manually validated.
When using the dataset, please cite the following preprint which provides details about the matching process:
Mongeon, P., Bowman, T. D., & Costas, R. (2022). An open dataset of scholars on Twitter (arXiv:2208.11065). arXiv. https://doi.org/10.48550/arXiv.2208.11065
Links to R scripts can be found here: https://github.com/pmongeon/scholars-on-twitter/
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe 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
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe 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
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe 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
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
Author-wise bibliometric analysis based on entropy.
No full textAuthor-wise bibliometric analysis based on entropy.</p
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