Efficiency Analysis of the Visibility of Latin American Universities and Their Impact on the Ranking Web

Torres-Samuel, Maritza; Vásquez, Carmen; Viloria, Amelec; Borrero, Tito Crissien; Varela, Noel; Cabrera, Danelys; Gaitán-Angulo, Mercedes; Lis-Gutiérrez, Jenny-Paola

doi:10.1007/978-3-319-93803-5_22

Cited by 16 publications

(9 citation statements)

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“…The proposed method shows the best lowest clustering results and outperforms in a few prior researches [20], [21] and [22]. As indicated in Table 7, all existing methods have their complexity using evolutionary strategy automatic clustering methods for determining the number of clusters automatically in k-means, while the proposed method uses technical-statistical control for problem-solving of ACDE as an automatic clustering strategy for finding the optimal number of clusters in k-means method.…”

Section: Data Transformation Stagementioning

confidence: 91%

RETRACTED CHAPTER: U-Control Chart Based Differential Evolution Clustering for Determining the Number of Cluster in k-Means

Silva

Lezama

Varela

et al. 2019

Green, Pervasive, and Cloud Computing

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The automatic clustering differential evolution (ACDE) is one of the clustering methods that are able to determine the cluster number automatically. However, ACDE still makes use of the manual strategy to determine k activation threshold thereby affecting its performance. In this study, the ACDE problem will be ameliorated using the u-control chart (UCC) then the cluster number generated from ACDE will be fed to k-means. The performance of the proposed method was tested using six public datasets from the UCI repository about academic efficiency (AE) and evaluated with Davies Bouldin Index (DBI) and Cosine Similarity (CS) measure. The results show that the proposed method yields excellent performance compared to prior researches.

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Section: Data Transformation Stagementioning

confidence: 91%

RETRACTED CHAPTER: U-Control Chart Based Differential Evolution Clustering for Determining the Number of Cluster in k-Means

Silva

Lezama

Varela

et al. 2019

Green, Pervasive, and Cloud Computing

Self Cite

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“…Selama satu dekade pembahasan Webometric terus meningkat khususnya pembahasan mengenai pengukuran dari setiap indikator dalam Webometric seperti, Presence (P), Visibility (V), Transparency (T), serta Excellence (E). Seperti dalam penelitian [12]- [16], peningkatan Webometric lebih ditekankan pada aspek Visibility dan Transparency. Pada [12], menunjukan bahwa peningkatan visibility melalui publikasi data akademis pada website universitas serta konten dan profil yang ditampilkan pada Google Scholar (GS).…”

Section: Penelitian Terkaitunclassified

“…Seperti dalam penelitian [12]- [16], peningkatan Webometric lebih ditekankan pada aspek Visibility dan Transparency. Pada [12], menunjukan bahwa peningkatan visibility melalui publikasi data akademis pada website universitas serta konten dan profil yang ditampilkan pada Google Scholar (GS). Selain memanfaatkan GS, [12] juga menyebutkan bahwa penggunaan sosial media yang bersifat scientific network seperti ResearchGate ataupun media sosial biasa seperti Facebook, Twitter dan Instagram terbukti efektif meningkatkan visibility universitas di Amerika Latin.…”

Section: Penelitian Terkaitunclassified

Strategi TIK untuk Meningkatkan Peringkat Webometric Universitas Riau Menggunakan Metode GAP Analysis

Daqiqil¹,

Andriani²,

Mahdiyah³

et al. 2021

SISTEMASI

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Webometrics merupakan sistem pemeringkatan Perguruan Tinggi berbasis website yang dapat digunakan sebagai indikator kinerja global sebuah universitas. UNRI sebagai institusi yang memiliki visi untuk menjadi universitas yang unggul di bidang riset terus berupaya meningkatkan peringkat Webometrics-nya. Namun dalam beberapa dekade terakhir, peringkat Webometric UNRI menurun dari peringkat 8 menjadi peringkat 35 dalam dua tahun terakhir. Oleh karena itu, penelitian ini bertujuan untuk melakukan analisis dan benchmark sehingga dihasilkan strategi TIK untuk meningkatkkan peringkat Webometric UNRI berdasarkan permasalahan yang dialami menggunakan metode SWOT dan Gap Analysis. Beberapa faktor utama yang menyebabkan menurunnya peringkat Webometric di antaranya adalah kurang efektifnya mekanisme tata kelola website sehingga banyak konten-konten yang tidak dapat diindek dengan baik oleh mesin pencari. Selain itu perubahan metodelogi penilaian Webometric juga memberikan pengaruh, dimana pada tahun 2019 Webometric menyeimbangkan porsi komponen aktifitas dan impact website. Hasil penelitian ini menghasilkan beberapa strategi yang kemudian diturunkan menjadi rencana aksi untuk meningkatkan peringkat UNRI di antaranya penguatan tata kelola website, implementasi kebijakan SEO dan Open Access, dan penggunaan aplikasi MY UNRI sebagai media berbagi tautan untuk meningkatkan nilai Visibility. Setelah melakukan implementasi beberapa strategi tersebut, maka peringkat Webometric UNRI periode Januari 2021 mengalami peningkatan dari peringkat 35 menjadi 31.

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“…Regarding the use of the Webometrics data, there are several researches that have already used them. For example, [7,8] compared different rankings like the Ranking of Shanghai, QS World University Ranking, SCimago Institutions Rankings SIR, and the Web Ranking of Universities-Webometrics, finding that the indicators associated with the research and institutional capacity stand out as common criteria in the reviewed evaluation methodologies. This research firstly states that Brazil occupies the first positions in the four rankings; and secondly, that there is a greater number of Latin American universities in QS (40%) and Webometrics (31%), while in the other two rankings it does not exceed 8%.…”

Section: Introductionmentioning

confidence: 99%

“…For its part, [8] and [10], used the Data Envelopment Analysis (DEA) for processing the academic data published on the website of each university, the content and profiles shown in Google Scholar (GS), the data published by the university in ResearchGate as scientific network, and finally, the data of social networks such as the Twitter and Facebook accounts of the corresponding institutions. The authors found that the postgraduate offer, visibility in GS, and the use of scientific and social networks contribute favorably to the web positioning of Latin American universities.…”

Section: Introductionmentioning

confidence: 99%

Determinants of ResearchGate (RG) Score for the Top100 of Latin American Universities at Webometrics

Henao-Rodríguez

Lis-Gutiérrez

Gaitán-Angulo

et al. 2019

Communications in Computer and Information Science

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This paper has the purpose of establishing the variables that explain the behavior of ResearchGate for the Top100 Latin American universities positioned in Webometrics database for January 2017. For this purpose, a search was carried out to get information about postgraduate courses and professors at the institutional websites and social networks, obtaining documents registered in Google Scholar. For the data analysis, the econometric technique of ordinary least squares was applied, a cross-sectional study for the year 2017 was conducted, and the individuals studied were the first 100 Latin American universities, obtaining a coefficient of determination of 73.82%. The results show that the most significant variables are the number of programs, the number of teacher's profiles registered in Google Scholar, the number of subscribers to the institutional YouTube channel, and the GDP per capita of the university origin country. Variables such as (i) number of undergraduate programs, (ii) number of scientific journals; (iii) number of documents found under the university domain; (iv) H-index of the 1st profile of researcher at the university; (vi) number of members of the institution; (v) SIR Scimago ranking of Higher Education Institutions; (vi) number of tweets published in the institutional account; (vii) number of followers in the Twitter institutional account; (vii) number of "likes" given to the institutional count, were not significant.

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Efficiency Analysis of the Visibility of Latin American Universities and Their Impact on the Ranking Web

Cited by 16 publications

References 10 publications

RETRACTED CHAPTER: U-Control Chart Based Differential Evolution Clustering for Determining the Number of Cluster in k-Means

RETRACTED CHAPTER: U-Control Chart Based Differential Evolution Clustering for Determining the Number of Cluster in k-Means

Strategi TIK untuk Meningkatkan Peringkat Webometric Universitas Riau Menggunakan Metode GAP Analysis

Determinants of ResearchGate (RG) Score for the Top100 of Latin American Universities at Webometrics

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