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  <front>
    <journal-meta>
      <journal-id journal-id-type="publisher-id">Oalib</journal-id>
      <journal-title-group>
        <journal-title>Open Access Library Journal</journal-title>
      </journal-title-group>
      <issn pub-type="epub">2333-9721</issn>
      <issn pub-type="ppub">2333-9705</issn>
      <publisher>
        <publisher-name>Scientific Research Publishing</publisher-name>
      </publisher>
    </journal-meta>
    <article-meta>
      <article-id pub-id-type="doi">10.4236/oalib.1114873</article-id>
      <article-id pub-id-type="publisher-id">Oalib-149480</article-id>
      <article-categories>
        <subj-group>
          <subject>Article</subject>
        </subj-group>
        <subj-group>
          <subject>Biomedical</subject>
          <subject>Life Sciences</subject>
          <subject>Business</subject>
          <subject>Economics</subject>
          <subject>Chemistry</subject>
          <subject>Materials Science</subject>
          <subject>Computer Science</subject>
          <subject>Communications</subject>
          <subject>Earth</subject>
          <subject>Environmental Sciences</subject>
          <subject>Engineering</subject>
          <subject>Medicine</subject>
          <subject>Healthcare</subject>
          <subject>Physics</subject>
          <subject>Mathematics</subject>
          <subject>Social Sciences</subject>
          <subject>Humanities</subject>
        </subj-group>
      </article-categories>
      <title-group>
        <article-title>Information Mining and Bibliometric Analysis of Academic Misconduct</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <name name-style="western">
            <surname>Wang</surname>
            <given-names>Yuenan</given-names>
          </name>
          <xref ref-type="aff" rid="aff1">1</xref>
        </contrib>
        <contrib contrib-type="author">
          <name name-style="western">
            <surname>Jiang</surname>
            <given-names>Tianxiao</given-names>
          </name>
          <xref ref-type="aff" rid="aff2">2</xref>
        </contrib>
        <contrib contrib-type="author">
          <name name-style="western">
            <surname>Zhai</surname>
            <given-names>Tong</given-names>
          </name>
          <xref ref-type="aff" rid="aff1">1</xref>
        </contrib>
        <contrib contrib-type="author" corresp="yes">
          <name name-style="western">
            <surname>Liu</surname>
            <given-names>Hongbin</given-names>
          </name>
          <xref ref-type="aff" rid="aff1">1</xref>
        </contrib>
      </contrib-group>
      <aff id="aff1"><label>1</label> Tianjin University Library, Tianjin University, Tianjin, China </aff>
      <aff id="aff2"><label>2</label> Tianjin Institute of Scientific&amp; Technical Information, Tianjin, China </aff>
      <author-notes>
        <fn fn-type="conflict" id="fn-conflict">
          <p>The authors have declared that no competing interests exist.</p>
        </fn>
      </author-notes>
      <pub-date pub-type="epub">
        <day>02</day>
        <month>02</month>
        <year>2026</year>
      </pub-date>
      <pub-date pub-type="collection">
        <month>02</month>
        <year>2026</year>
      </pub-date>
      <volume>13</volume>
      <issue>02</issue>
      <fpage>1</fpage>
      <lpage>14</lpage>
      <history>
        <date date-type="received">
          <day>14</day>
          <month>01</month>
          <year>2026</year>
        </date>
        <date date-type="accepted">
          <day>06</day>
          <month>02</month>
          <year>2026</year>
        </date>
        <date date-type="published">
          <day>09</day>
          <month>02</month>
          <year>2026</year>
        </date>
      </history>
      <permissions>
        <copyright-statement>© 2026 by the authors and Scientific Research Publishing Inc.</copyright-statement>
        <copyright-year>2026</copyright-year>
        <license license-type="open-access">
          <license-p> This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( <ext-link ext-link-type="uri" xlink:href="https://creativecommons.org/licenses/by/4.0/">https://creativecommons.org/licenses/by/4.0/</ext-link> ). </license-p>
        </license>
      </permissions>
      <self-uri content-type="doi" xlink:href="https://doi.org/10.4236/oalib.1114873">https://doi.org/10.4236/oalib.1114873</self-uri>
      <abstract>
        <p>Academic misconduct has always been a hot topic both internationally and domestically, and there have been many studies on it. The present bibliometric analysis was conducted on the basis of 1562 WOS database-derived papers to shed more light on publication performances as well as research features of Academic Misconduct. We used indicators for evaluating impacts of the most prolific journals, countries/territories, organizations and authors. Additionally, interactions across prolific countries/territories, organizations, authors and keywords were assessed and visualized through social network analysis by adopting VOSviewer software. Our findings shed more light on summarizing the research status in the field of academic misconduct-related fields.</p>
      </abstract>
      <kwd-group kwd-group-type="author-generated" xml:lang="en">
        <kwd>Information Mining</kwd>
        <kwd>Bibliometric Analysis</kwd>
        <kwd>Academic Misconduct</kwd>
        <kwd>Scholarly Misconduct</kwd>
        <kwd>VOSviewer</kwd>
      </kwd-group>
    </article-meta>
  </front>
  <body>
    <sec id="sec1">
      <title>1. Introduction</title>
      <p>Scholarly misconduct causes significant impact on the academic community. To extremes, results of scholarly misconduct could endanger public welfare as well as national security [<xref ref-type="bibr" rid="B1">1</xref>]. The scientiﬁc misconduct subject is under extensive discussion in academic journals, but many papers on the specific topic are letters or editorials. Additionally, many papers focused on analyzing the scientiﬁc misconduct scope [<xref ref-type="bibr" rid="B2">2</xref>]. Scientiﬁc misconduct has aroused increasing interest in science policy makers, researchers, and the whole society. The consequences may comprise efficient location of research funds because of forged clinical studies affecting clinical practice and overinﬂated curricula vitae [<xref ref-type="bibr" rid="B3">3</xref>]. Additionally, the scientiﬁc misconduct cases have an unfavorable influence on society if they are public [<xref ref-type="bibr" rid="B4">4</xref>][<xref ref-type="bibr" rid="B5">5</xref>]. With the undermining of confidence, researchers and institutions will have reduced reputations. The definition of scientiﬁc misconduct is complicated since some readers suggest that it just involves data distortion and fabrication, whereas others suggest that it involves plagiarism by stealing ideas of others [<xref ref-type="bibr" rid="B6">6</xref>]. However, scientiﬁc misconduct has been increasingly suggested to involve more unethical behaviors such as including authors not contributing to studies, not declaring conﬂicts of interest, or publishing one article in diverse journals, also called self-plagiarism [<xref ref-type="bibr" rid="B4">4</xref>].</p>
      <p>Bibliometrics has been the efficient approach used in the quantitative evaluation of the current scientific production status and development in a certain study ﬁeld [<xref ref-type="bibr" rid="B7">7</xref>][<xref ref-type="bibr" rid="B8">8</xref>]. It is used in different areas like solid waste [<xref ref-type="bibr" rid="B9">9</xref>], computer science [<xref ref-type="bibr" rid="B10">10</xref>], clinical medicine [<xref ref-type="bibr" rid="B11">11</xref>], proteomics [<xref ref-type="bibr" rid="B12">12</xref>], and river water quality [<xref ref-type="bibr" rid="B13">13</xref>] and so on. Traditional indicators are subject category, publication output, journal, author, contributing country and institution. There are five recent indicators developed for evaluating country and institution performances, namely, ﬁrst-author, total, corresponding-author, as well as collaborative publications [<xref ref-type="bibr" rid="B14">14</xref>]-[<xref ref-type="bibr" rid="B16">16</xref>]. Keywords are analyzed for examining research trends and hotspots recently [<xref ref-type="bibr" rid="B17">17</xref>][<xref ref-type="bibr" rid="B18">18</xref>].</p>
      <p>In our study, we meticulously gather bibliographic information for all retrieved studies, and we then employ knowledge mapping techniques for analysis, utilizing VOSviewer, a tool renowned for its ability to transform bibliometric data into easily understandable visual formats [<xref ref-type="bibr" rid="B19">19</xref>]. Through VOSviewer, we conduct network analyses focusing on several aspects: author keyword co-occurrence, the journal and author co-citation, and the co-authorship networks that encompass the institutions and countries of the authors. This method includes generating link strengths to better understand the relationships within the data. This approach is instrumental in delineating and structuring the subject area’s scope, enhancing our comprehension of the field. Additionally, we adopt the fractional counting approach for its effectiveness in offering field-normalized visual representations [<xref ref-type="bibr" rid="B20">20</xref>]. Visualizing networks such as the co-occurrence network of keywords, journal and author co-citation network, and co-authorship networks of institutions, countries, and authors, this method facilitates an exhaustive examination of the research status in this field [<xref ref-type="bibr" rid="B21">21</xref>].</p>
    </sec>
    <sec id="sec2">
      <title>2. Methodology and Source Data</title>
      <p>We retrieved publication data in the present work using Science Citation Index Expanded (SCIE) and Social Sciences Citation Index (SSCI) from online Web of Science Core Collection database. It represents the frequently utilized data source to retrieve bibliometric documents. All papers on academic misconduct were searched according to topic (title, abstract, keywords plus, and author keywords). Data were cleaned using duplicate, whereas unrelated data were eliminated by initial title, abstract and keyword screening. Only “Article” and “Review” were searched. As mentioned earlier, there were 1562 papers on academic misconduct from 2004 to 2023 in SCIE and SSCI. Data from a total of 1562 papers were obtained based on Web of Science Core Collection. The software used to construct and visualize bibliometric networks was employed for data analysis [<xref ref-type="bibr" rid="B22">22</xref>]-[<xref ref-type="bibr" rid="B27">27</xref>].</p>
    </sec>
    <sec id="sec3">
      <title>3. Results and Discussion</title>
      <sec id="sec3dot1">
        <title>3.1. Research Output Trend</title>
        <p><xref ref-type="fig" rid="fig1">Figure 1</xref><xref ref-type="fig" rid="fig1">Figure 1</xref> displays annual number of publications. In 2004, 20 papers were on academic misconduct. During the twenty years, the published papers showed a steady increasing trend, but in 2021, the number decreased slightly and decreased to 115. In 2023, it reached the highest value of 190. The continuous increase in the number of papers indicates the growing global interest and development in academic misconduct research.</p>
        <fig id="fig1">
          <label>Figure 1</label>
          <graphic xlink:href="https://html.scirp.org/file/1114873-rId13.jpeg?20260209020510" />
        </fig>
        <p><bold>Figure 1.</bold> Publication trends of papers published each year.</p>
      </sec>
      <sec id="sec3dot2">
        <title>3.2. Distribution of Subject Categories</title>
        <p><xref ref-type="fig" rid="fig2">Figure 2</xref><xref ref-type="fig" rid="fig2">Figure 2</xref> shows the distribution of 1562 papers in the top 10 research fields. Many documents were in “Education &amp; Educational Research” field, occupying 9.15% of the whole number. The other four research fields were Psychology (5.95%), Science &amp; Technology—Other Topics (3.78%), Social Sciences—Other Topics, Engineering; History &amp; Philosophy of Science, Science &amp; Technology—Other Topics; Philosophy (3.65%) and General &amp; Internal Medicine (3.33%).</p>
      </sec>
      <sec id="sec3dot3">
        <title>3.3. Important Journals</title>
        <p>The papers on academic misconduct were published in 449 journals. According to article and citation numbers in each journal, we have determined in our study which 10 journals have contributed most significantly to the field of academic misconduct (<bold>Table 1</bold>). The 273 papers published by these prestigious journals</p>
        <fig id="fig2">
          <label>Figure 2</label>
          <graphic xlink:href="https://html.scirp.org/file/1114873-rId14.jpeg?20260209020510" />
        </fig>
        <p><bold>Figure 2.</bold> Distribution of 1562 papers in the top 10 research fields.</p>
        <p>together account for 60.8% of all publications in this discipline. <italic>Science and Engineering Ethics</italic> stands out as the leading journal with more articles totaling 57. With 52 and 51 publications, <italic>Academy of Management Discoveries</italic>and<italic>Ethics</italic><italic>Behavior</italic> comes second and third among the 10 most prolific journals separately. Among those 10 most prolific journals, papers published in <italic>PLOS One</italic> had highest total citations which have been cited 1371 times, with the greatest mean citation frequency reaching 72.16 times. The number of total citations of <italic>Science and Engineering Ethics</italic> and <italic>Ethics and Behavior</italic> was second and third, respectively, but both papers have fewer citations per article. Notably, journals with fewer publications, such as<italic>Studies</italic><italic>in</italic><italic>Higher Education</italic>, <italic>Assessment and Evaluation in</italic><italic>Higher Education</italic>, <italic>Frontiers in Psychology</italic>and <italic>Higher Education</italic> have amassed a considerable amount of citations per article. This emphasizes how highly significant the articles published in these journals are from an academic standpoint.</p>
        <p><bold>Table 1.</bold> Features of those 10 most prolific journals for research regarding academic misconduct.</p>
        <table-wrap id="tbl1">
          <label>Table 1</label>
          <table>
            <tbody>
              <tr>
                <td>Journals</td>
                <td>Articles</td>
                <td>Citations</td>
                <td>Citations per article</td>
                <td>IF5</td>
              </tr>
              <tr>
                <td>Science and Engineering Ethics</td>
                <td>57</td>
                <td>1254</td>
                <td>22</td>
                <td>3.5</td>
              </tr>
              <tr>
                <td>Academy of Management Discoveries</td>
                <td>52</td>
                <td>520</td>
                <td>10</td>
                <td>6.6</td>
              </tr>
              <tr>
                <td>Ethics and Behavior</td>
                <td>51</td>
                <td>1224</td>
                <td>24</td>
                <td>2.1</td>
              </tr>
              <tr>
                <td>Assessment and Evaluation in Higher Education</td>
                <td>22</td>
                <td>728</td>
                <td>33.09</td>
                <td>5.2</td>
              </tr>
              <tr>
                <td>PLOS One</td>
                <td>19</td>
                <td>1371</td>
                <td>72.16</td>
                <td>3.3</td>
              </tr>
              <tr>
                <td>Studies in Higher Education</td>
                <td>17</td>
                <td>642</td>
                <td>37.76</td>
                <td>4.8</td>
              </tr>
              <tr>
                <td>Scientometrics</td>
                <td>17</td>
                <td>433</td>
                <td>25.47</td>
                <td>3.8</td>
              </tr>
              <tr>
                <td>Journal of Forensic Sciences</td>
                <td>14</td>
                <td>188</td>
                <td>13.43</td>
                <td>1.6</td>
              </tr>
              <tr>
                <td>Frontiers in Psychology</td>
                <td>12</td>
                <td>382</td>
                <td>31.83</td>
                <td>3.3</td>
              </tr>
              <tr>
                <td>Higher Education</td>
                <td>12</td>
                <td>395</td>
                <td>32.92</td>
                <td>5.0</td>
              </tr>
            </tbody>
          </table>
        </table-wrap>
        <p>IF5: 5-year impact factor.</p>
        <p><xref ref-type="fig" rid="fig3">Figure 3</xref><xref ref-type="fig" rid="fig3">Figure 3</xref> shows the values of citations per article and 5-year impact factor (IF5) for those 10 most prolific journals. Obviously, the variation trend average citation values were inconsistent with journal IF5, especially for <italic>PLOS One</italic> whose IF5 took the 7th place among 10 most prolific journals, but the average citation value was the highest. In addition, IF5 of <italic>Academy of Management Discoveries</italic> ranks first among those 10 most prolific journals, but the average citation value was lowest.</p>
        <fig id="fig3">
          <label>Figure 3</label>
          <graphic xlink:href="https://html.scirp.org/file/1114873-rId15.jpeg?20260209020510" />
        </fig>
        <p><bold>Figure 3.</bold> Paper average citations values and 5-year impact factor for those 10 most prolific journals.</p>
      </sec>
      <sec id="sec3dot4">
        <title>3.4. Contribution of Countries and Organizations</title>
        <p>Those 15 most prolific countries/territories were investigated for their international collaborations (<bold>Table 2</bold>). During 2004-2023, the USA, England, China, Australia and Germany emerged as the leading countries regarding the overall number of publications within the field of academic misconduct. The USA tops the list with 530 documents, which have been cited 15205 times. England and China follow with 150 publications and 4115 citations, and 147 publications and 2341 citations respectively. Canada has the highest Average Citations (AC = 50.26). Australia is second (AC = 30.88). The presence of countries from different continents, Asia (China), Europe (England, Germany, Italy, Belgium, France, The Netherlands), Australia and America (USA, Canada), among the top 10 contributors, underscores the global significance of this research topic.</p>
        <p>Link represents the indicator (VOSviewer) that indicates the connection number of a factor (like one country/territory) with others (like additional 14 countries/territories). For those 15 most prolific countries/territories, their links were 14, indicating the close collaborations among them. Total Link Strength (TLS) also stands for an indicator (VOSviewer) adopted for representing collaboration strength of selected factors (countries/territories). The collaborative state among these countries, as illustrated in <bold>Table 2</bold>, indicates that the USA, with the highest link strength of 139, maintains extensive connections with numerous countries, particularly England, Germany, Canada and China. These four countries alone account for 50% of USA’s total link strength, emphasizing strong international collaborations. <xref ref-type="fig" rid="fig4">Figure 4</xref><xref ref-type="fig" rid="fig4">Figure 4</xref> shows visualization of international collaborations among the 15 most prolific countries/territories. When visualizing the network, the circle size for one item could be analyzed through the item weight, with a greater item weight indicating a larger circle. Additionally, the link strength was the highest between USA and England. Of those 10 most significant link strength combinations, there were 6 combinations related to USA. USA had a pivotal role in such collaborations, suggesting the research potential in academic misconduct. Colors in <xref ref-type="fig" rid="fig4">Figure 4</xref><xref ref-type="fig" rid="fig4">Figure 4</xref> can differentiate diverse clusters (with one cluster indicating one set of tightly associated nodes).</p>
        <fig id="fig4">
          <label>Figure 4</label>
          <graphic xlink:href="https://html.scirp.org/file/1114873-rId16.jpeg?20260209020510" />
        </fig>
        <p><bold>Figure 4.</bold> International collaborations among 15 most prolific countries/territories.</p>
        <p><bold>Table 2.</bold> The 15 most prolific countries and relevant indicators.</p>
        <table-wrap id="tbl2">
          <label>Table 2</label>
          <table>
            <tbody>
              <tr>
                <td>Country/Territory</td>
                <td>TP</td>
                <td>TC</td>
                <td>AC</td>
                <td>TLS</td>
                <td>Links</td>
              </tr>
              <tr>
                <td>USA</td>
                <td>530</td>
                <td>15,205</td>
                <td>28.69</td>
                <td>139</td>
                <td>14</td>
              </tr>
              <tr>
                <td>England</td>
                <td>150</td>
                <td>4115</td>
                <td>27.43</td>
                <td>92</td>
                <td>14</td>
              </tr>
              <tr>
                <td>China</td>
                <td>147</td>
                <td>2341</td>
                <td>15.93</td>
                <td>57</td>
                <td>13</td>
              </tr>
              <tr>
                <td>Australia</td>
                <td>91</td>
                <td>2810</td>
                <td>30.88</td>
                <td>47</td>
                <td>14</td>
              </tr>
              <tr>
                <td>Germany</td>
                <td>77</td>
                <td>1068</td>
                <td>13.87</td>
                <td>59</td>
                <td>13</td>
              </tr>
              <tr>
                <td>Canada</td>
                <td>76</td>
                <td>3820</td>
                <td>50.26</td>
                <td>58</td>
                <td>14</td>
              </tr>
              <tr>
                <td>Spain</td>
                <td>64</td>
                <td>1101</td>
                <td>17.20</td>
                <td>24</td>
                <td>8</td>
              </tr>
              <tr>
                <td>India</td>
                <td>54</td>
                <td>465</td>
                <td>8.61</td>
                <td>32</td>
                <td>14</td>
              </tr>
              <tr>
                <td>Netherlands</td>
                <td>48</td>
                <td>1417</td>
                <td>29.52</td>
                <td>52</td>
                <td>13</td>
              </tr>
              <tr>
                <td>France</td>
                <td>43</td>
                <td>1287</td>
                <td>29.93</td>
                <td>41</td>
                <td>14</td>
              </tr>
              <tr>
                <td>Italy</td>
                <td>39</td>
                <td>610</td>
                <td>15.64</td>
                <td>35</td>
                <td>14</td>
              </tr>
              <tr>
                <td>Belgium</td>
                <td>37</td>
                <td>733</td>
                <td>19.81</td>
                <td>45</td>
                <td>13</td>
              </tr>
              <tr>
                <td>Brazil</td>
                <td>29</td>
                <td>515</td>
                <td>17.76</td>
                <td>30</td>
                <td>14</td>
              </tr>
              <tr>
                <td>Switzerland</td>
                <td>27</td>
                <td>713</td>
                <td>26.41</td>
                <td>28</td>
                <td>13</td>
              </tr>
              <tr>
                <td>South Africa</td>
                <td>25</td>
                <td>537</td>
                <td>21.48</td>
                <td>29</td>
                <td>13</td>
              </tr>
            </tbody>
          </table>
        </table-wrap>
        <p>TP, the number of publications; TC, Total Citations; AC, Average Citations; TLS, Total Link Strength.</p>
        <p><bold>Table 3</bold> displays primary performance for 15 most prolific organizations. Of them, eight organizations were in USA, three in China, two in Netherlands and one each in Canada and England. University of Pennsylvania takes the leading position in Total Publications (TP = 16). With regard to institutions, the University of Montreal, University of Pennsylvania, University of Michigan, Leidin University and University of Illinois are identified as the top five in research based on citation numbers. However, University of Montreal was dominant in total citations (TC = 660) and Average Citations (AC = 60). The second is the Leidin University (AC = 41.25) and the third is University of Michigan (AC=40.25). The links of University of Pennsylvania are 12, which indicates the collaboration of the university with an additional 12 organizations. From <xref ref-type="fig" rid="fig5">Figure 5</xref><xref ref-type="fig" rid="fig5">Figure 5</xref>, collaborations could be visualized between the top 15 organizations, with different colors indicating diverse clusters.</p>
      </sec>
      <sec id="sec3dot5">
        <title>3.5. Influential Authors</title>
        <p>We investigated the global distribution of 1562 papers. From <bold>Table 4</bold>, USA is the first prolific country/territory according to first author and CA. USA is advantageous relative to other countries/territories. Hu, Guangwei published the most papers, followed by Resnik, David B. and Casadevall, Arturo. Fanelli, Daniele has the highest average citation count, followed by Fang, Ferric C. and Casadevall, Arturo.</p>
        <fig id="fig5">
          <label>Figure 5</label>
          <graphic xlink:href="https://html.scirp.org/file/1114873-rId17.jpeg?20260209020510" />
        </fig>
        <p><bold>Figure 5.</bold> Co-occurrence network of those top 15 prolific organizations.</p>
        <p><bold>Table 3.</bold> The 15 most prolific organizations and relevant indicators.</p>
        <table-wrap id="tbl3">
          <label>Table 3</label>
          <table>
            <tbody>
              <tr>
                <td>Organizations/Institutions</td>
                <td>Country</td>
                <td>TP</td>
                <td>TC</td>
                <td>AC</td>
                <td>TLS</td>
                <td>Links</td>
              </tr>
              <tr>
                <td>University of Pennsylvania</td>
                <td>USA</td>
                <td>16</td>
                <td>510</td>
                <td>31.87</td>
                <td>13</td>
                <td>12</td>
              </tr>
              <tr>
                <td>Hong Kong Polytech University</td>
                <td>China</td>
                <td>13</td>
                <td>108</td>
                <td>8.31</td>
                <td>13</td>
                <td>6</td>
              </tr>
              <tr>
                <td>University of Michigan</td>
                <td>USA</td>
                <td>12</td>
                <td>483</td>
                <td>40.25</td>
                <td>11</td>
                <td>10</td>
              </tr>
              <tr>
                <td>Northwestern University</td>
                <td>USA</td>
                <td>11</td>
                <td>231</td>
                <td>21</td>
                <td>11</td>
                <td>9</td>
              </tr>
              <tr>
                <td>University of Montreal</td>
                <td>Canada</td>
                <td>11</td>
                <td>660</td>
                <td>60</td>
                <td>10</td>
                <td>9</td>
              </tr>
              <tr>
                <td>University of Manchester</td>
                <td>England</td>
                <td>11</td>
                <td>284</td>
                <td>25.82</td>
                <td>9</td>
                <td>5</td>
              </tr>
              <tr>
                <td>University of Amsterdam</td>
                <td>Netherlands</td>
                <td>9</td>
                <td>185</td>
                <td>20.56</td>
                <td>8</td>
                <td>4</td>
              </tr>
              <tr>
                <td>Chinese Academy of Sciences</td>
                <td>China</td>
                <td>9</td>
                <td>186</td>
                <td>20.67</td>
                <td>7</td>
                <td>3</td>
              </tr>
              <tr>
                <td>University of Illinois</td>
                <td>USA</td>
                <td>8</td>
                <td>308</td>
                <td>38.5</td>
                <td>7</td>
                <td>7</td>
              </tr>
              <tr>
                <td>Leidin University</td>
                <td>Netherlands</td>
                <td>8</td>
                <td>330</td>
                <td>41.25</td>
                <td>7</td>
                <td>6</td>
              </tr>
              <tr>
                <td>University of Maryland</td>
                <td>USA</td>
                <td>7</td>
                <td>161</td>
                <td>23</td>
                <td>9</td>
                <td>8</td>
              </tr>
              <tr>
                <td>Indiana University</td>
                <td>USA</td>
                <td>7</td>
                <td>185</td>
                <td>26.43</td>
                <td>7</td>
                <td>7</td>
              </tr>
              <tr>
                <td>Johns Hopkins Bloomberg School of Public Health</td>
                <td>USA</td>
                <td>7</td>
                <td>238</td>
                <td>34</td>
                <td>8</td>
                <td>6</td>
              </tr>
              <tr>
                <td>Huanggang Normal University</td>
                <td>China</td>
                <td>6</td>
                <td>37</td>
                <td>6.17</td>
                <td>8</td>
                <td>3</td>
              </tr>
              <tr>
                <td>Yale University</td>
                <td>USA</td>
                <td>5</td>
                <td>90</td>
                <td>18</td>
                <td>8</td>
                <td>8</td>
              </tr>
            </tbody>
          </table>
        </table-wrap>
        <p><bold>Table 4.</bold> The 15 most prolific authors.</p>
        <table-wrap id="tbl4">
          <label>Table 4</label>
          <table>
            <tbody>
              <tr>
                <td>Author</td>
                <td>Country/Territory</td>
                <td>Organizations/Institutions</td>
                <td>TP</td>
                <td>TC</td>
                <td>AC</td>
              </tr>
              <tr>
                <td>Hu, Guangwei</td>
                <td>China</td>
                <td>Huanggang Normal University; Hong Kong Polytechnic University</td>
                <td>17</td>
                <td>299</td>
                <td>17.59</td>
              </tr>
              <tr>
                <td>Resnik, David B.</td>
                <td>USA</td>
                <td>National Institutes of Health (NIH)</td>
                <td>9</td>
                <td>228</td>
                <td>25.33</td>
              </tr>
              <tr>
                <td>Casadevall, Arturo</td>
                <td>USA</td>
                <td>University of Washington</td>
                <td>7</td>
                <td>949</td>
                <td>135.57</td>
              </tr>
              <tr>
                <td>Fang, Ferric C.</td>
                <td>USA</td>
                <td>University of Washington</td>
                <td>6</td>
                <td>949</td>
                <td>158.17</td>
              </tr>
              <tr>
                <td>Marusic, Ana</td>
                <td>Croatia</td>
                <td>University of Split</td>
                <td>6</td>
                <td>178</td>
                <td>29.67</td>
              </tr>
              <tr>
                <td>Ruano-Ravina, Alberto</td>
                <td>Spain</td>
                <td>Universidad de Santiago de Compostela</td>
                <td>6</td>
                <td>130</td>
                <td>21.67</td>
              </tr>
              <tr>
                <td>Yang, Shu Ching</td>
                <td>China</td>
                <td>National Sun Yat Sen University</td>
                <td>6</td>
                <td>92</td>
                <td>15.33</td>
              </tr>
              <tr>
                <td>Fanelli, Daniele</td>
                <td>USA</td>
                <td>University of Montreal</td>
                <td>5</td>
                <td>988</td>
                <td>197.6</td>
              </tr>
              <tr>
                <td>Van Houtte, Mieke</td>
                <td>Netherlands</td>
                <td>Ghent University</td>
                <td>5</td>
                <td>272</td>
                <td>54.4</td>
              </tr>
              <tr>
                <td>Lei, Jun</td>
                <td>Singapore</td>
                <td>Nanyang Technological University; National Institute of Education (NIE) Singapore</td>
                <td>5</td>
                <td>184</td>
                <td>36.8</td>
              </tr>
              <tr>
                <td>Tang, Bor Luen</td>
                <td>Singapore</td>
                <td>National University of Singapore</td>
                <td>5</td>
                <td>105</td>
                <td>21</td>
              </tr>
              <tr>
                <td>Hofmann, Bjorn</td>
                <td>Norway</td>
                <td>University of Oslo; Norwegian University of Science &amp; Technology (NTNU)</td>
                <td>5</td>
                <td>80</td>
                <td>16</td>
              </tr>
              <tr>
                <td>Holm, Soren</td>
                <td>USA</td>
                <td>University of Manchester</td>
                <td>5</td>
                <td>80</td>
                <td>16</td>
              </tr>
              <tr>
                <td>Mahadi, Zurina</td>
                <td>Malaysia</td>
                <td>Universiti Kebangsaan Malaysia</td>
                <td>5</td>
                <td>38</td>
                <td>7.6</td>
              </tr>
              <tr>
                <td>Amin, Latifah</td>
                <td>Malaysia</td>
                <td>Universiti Kebangsaan Malaysia</td>
                <td>5</td>
                <td>38</td>
                <td>7.6</td>
              </tr>
            </tbody>
          </table>
        </table-wrap>
        <p>From <xref ref-type="fig" rid="fig6">Figure 6</xref><xref ref-type="fig" rid="fig6">Figure 6</xref>, the author’s co-citation network map plays a crucial role in understanding the interconnections among authors in the field of academic misconduct. From a total of 4510 authors, 1000 were selected for this map according to the minimum citation threshold of 20. This map organizes these authors in six distinct clusters, each representing a group of authors frequently cited in the literature. The largest cluster is represented in red, encompassing 8 authors, with Resnik, David B. standing out as the leading figure. The second cluster, shown in yellow, includes 6 authors. Notably, Arturo Casadevall is prominent within this cluster. The third cluster, shown in deep blue, includes 6 authors. and Ruano-Ravina, Alberto is prominent within this cluster. Each cluster within this map features key authors who act as focal points, around whom other authors are positioned. These individuals are significant contributors to the field, as indicated by their positioning and link strengths in the co-citation network, highlighting their influence and importance in the field of academic misconduct.</p>
        <fig id="fig6">
          <label>Figure 6</label>
          <graphic xlink:href="https://html.scirp.org/file/1114873-rId18.jpeg?20260209020510" />
        </fig>
        <p><bold>Figure 6.</bold> Co-citation network analysis of the top 15 most productive authors.</p>
      </sec>
      <sec id="sec3dot6">
        <title>3.6. Research Themes</title>
        <p>Author keywords represent the literature essence and core, which demonstrate the most interesting areas for researchers. In our research on academic misconduct, we employed co-occurrence network analysis on author keywords for discerning primary research priorities and interests globally. This analysis reveals the most frequently used keywords and their interconnections, providing insights into the dominant themes in this research area. <bold>Table 5</bold> displays author keywords (occurrences ≥ 10) and corresponding total link strengths. Of them, “plagiarism” associated words had the highest occurrence, occurring 266 times. In particular, “plagiarism” also has the highest total link strength, illustrating “plagiarism” as a keyword tightly related to others. “Academic dishonesty” is the second-most common word that appears (129 occurrences). Other significant keywords include “scientific misconduct” (85 occurrences), “research misconduct” (80), “academic integrity” (75), “cheating” (73), “ethics” (67), “academic misconduct” (46), “research integrity” (43), and “misconduct” (40). The co-occurrence network demonstrates strong connections between academic misconduct and key areas like plagiarism, academic dishonesty and scientific misconduct.</p>
        <p><bold>Table 5.</bold> List of author keywords (occurrences ≥ 10) and corresponding total link strengths.</p>
        <table-wrap id="tbl5">
          <label>Table 5</label>
          <table>
            <tbody>
              <tr>
                <td>Author keywords</td>
                <td>Occurrences</td>
                <td>TLS</td>
                <td>Author keywords</td>
                <td>Occurrences</td>
                <td>TLS</td>
              </tr>
              <tr>
                <td>Plagiarism</td>
                <td>266</td>
                <td>372</td>
                <td>Retraction</td>
                <td>29</td>
                <td>25</td>
              </tr>
              <tr>
                <td>Academic dishonesty</td>
                <td>129</td>
                <td>138</td>
                <td>Education</td>
                <td>18</td>
                <td>25</td>
              </tr>
              <tr>
                <td>Cheating</td>
                <td>73</td>
                <td>131</td>
                <td>Academic honesty</td>
                <td>14</td>
                <td>24</td>
              </tr>
              <tr>
                <td>Scientific misconduct</td>
                <td>85</td>
                <td>127</td>
                <td>Turnitin</td>
                <td>11</td>
                <td>23</td>
              </tr>
              <tr>
                <td>Research misconduct</td>
                <td>80</td>
                <td>113</td>
                <td>Authorship</td>
                <td>12</td>
                <td>22</td>
              </tr>
              <tr>
                <td>Academic integrity</td>
                <td>75</td>
                <td>110</td>
                <td>Scientific integrity</td>
                <td>15</td>
                <td>21</td>
              </tr>
              <tr>
                <td>Ethics</td>
                <td>67</td>
                <td>101</td>
                <td>Attitudes</td>
                <td>12</td>
                <td>21</td>
              </tr>
              <tr>
                <td>Research integrity</td>
                <td>43</td>
                <td>77</td>
                <td>Research</td>
                <td>10</td>
                <td>21</td>
              </tr>
              <tr>
                <td>Misconduct</td>
                <td>40</td>
                <td>66</td>
                <td>Meta-analysis</td>
                <td>17</td>
                <td>20</td>
              </tr>
              <tr>
                <td>Academic misconduct</td>
                <td>46</td>
                <td>59</td>
                <td>Integrity</td>
                <td>10</td>
                <td>20</td>
              </tr>
              <tr>
                <td>Research ethics</td>
                <td>32</td>
                <td>53</td>
                <td>University students</td>
                <td>12</td>
                <td>17</td>
              </tr>
              <tr>
                <td>Fabrication</td>
                <td>17</td>
                <td>53</td>
                <td>Knowledge</td>
                <td>12</td>
                <td>17</td>
              </tr>
              <tr>
                <td>Falsification</td>
                <td>37</td>
                <td>52</td>
                <td>Methodology</td>
                <td>11</td>
                <td>16</td>
              </tr>
              <tr>
                <td>Higher education</td>
                <td>33</td>
                <td>50</td>
                <td>Iran</td>
                <td>12</td>
                <td>15</td>
              </tr>
              <tr>
                <td>Fraud</td>
                <td>24</td>
                <td>41</td>
                <td>Gender</td>
                <td>11</td>
                <td>15</td>
              </tr>
              <tr>
                <td>Dishonesty</td>
                <td>19</td>
                <td>34</td>
                <td>Trust</td>
                <td>20</td>
                <td>14</td>
              </tr>
              <tr>
                <td>Self-plagiarism</td>
                <td>20</td>
                <td>31</td>
                <td>Systematic review</td>
                <td>13</td>
                <td>14</td>
              </tr>
              <tr>
                <td>Students</td>
                <td>14</td>
                <td>31</td>
                <td>Plagiarism detection</td>
                <td>19</td>
                <td>9</td>
              </tr>
              <tr>
                <td>Retractions</td>
                <td>19</td>
                <td>28</td>
                <td>Distrust</td>
                <td>12</td>
                <td>9</td>
              </tr>
              <tr>
                <td>Academic writing</td>
                <td>16</td>
                <td>26</td>
                <td>Covid-19</td>
                <td>10</td>
                <td>5</td>
              </tr>
              <tr>
                <td>Publication ethics</td>
                <td>16</td>
                <td>26</td>
                <td>
                </td>
                <td>
                </td>
                <td>
                </td>
              </tr>
            </tbody>
          </table>
        </table-wrap>
        <p><xref ref-type="fig" rid="fig7">Figure 7</xref><xref ref-type="fig" rid="fig7">Figure 7</xref> exhibits co-occurrence network of author keywords with highest occurrence frequency. The 41 authors’ keyword network (occurrences ≥ 10) was displayed. Typically, these 41 author keywords were classified into six groups, with one color indicating one group. During network visualization, the item cluster indicated author keyword color based on VOSviewer. The first cluster comprises 10 keywords, including but not limited to ethics, misconduct, dishonesty, integrity and falsification. The second cluster, which has 10 keywords, predominantly features terms like fraud, retractions, self-plagiarism and authorship. The remaining clusters, the third, fourth, fifth and sixth, contain 9, 5, 4 and 3 keywords respectively. This keyword analysis underscores the diverse and interconnected aspects of academic misconduct, highlighting the key areas of focus and interest within the global research community.</p>
        <fig id="fig7">
          <label>Figure 7</label>
          <graphic xlink:href="https://html.scirp.org/file/1114873-rId19.jpeg?20260209020510" />
        </fig>
        <p><bold>Figure 7.</bold> Co-occurrence network of author keywords with the highest occurrence frequency.</p>
      </sec>
    </sec>
    <sec id="sec4">
      <title>4. Conclusion</title>
      <p>The present work used a bibliometric approach for analyzing papers from Web of Science Core Collection database. Besides, impacts of most prolific journals, countries/territories, organizations and authors were assessed. Results showed the scientiﬁc output in the field of academic misconduct research increased steadily in the last twenty years. In these 1562 publications, Education &amp; Educational Research, Psychology, and Science &amp; Technology—Other Topics ranked the top among main subject categories. Papers on academic misconduct were published in 449 journals. <italic>Science</italic><italic>a</italic><italic>nd Engineering Ethics</italic> stands out as the leading journal. The interactions among productive countries/territories, organizations, authors and keywords were analyzed. With regard to countries/territories, USA published the most papers and had the greatest total citations; Canada had the greatest average citations. At an institutional level, University of Pennsylvania was the most prolific organization with the greatest total number of articles. University of Montreal had the greatest total citations and average citations. USA played a key role in international collaborations, suggesting the research potential in academic misconduct. For organizations, University of Pennsylvania has the highest collaboration intensity. For authors, Hu, Guangwei (Huanggang Normal University; Hong Kong Polytechnic University) was the most prolific author and Fanelli, Daniele (University of Montreal) has the highest total citations and average citations. Resnik, David B. has the most collaborators. “plagiarism”, “academic dishonesty”, “scientific misconduct”, “research misconduct” and “academic integrity” were the most frequent author keywords. VOSviewer was adopted for visualizing relation networks of prolific countries/territories, organizations, authors and keywords. Our research findings serve as a valuable resource for researchers, such as complete knowledge regarding leading journals, countries/territories, and institutions in this relevant research area, so as to instruct paper submission, academic exchange and collaboration and offering them essential insights into the topic to shape future research directions. Based on such high-quality papers, readers can obtain efficient knowledge, like theory, methods, and tools, and acquire research frontiers and hotspots for finding the key issues for scholars. Overall, conducting a bibliometric study on academic misconduct field offers a systematic approach to understanding the state of the field, identifying research trends and guiding future research efforts.</p>
    </sec>
    <sec id="sec5">
      <title>Author Contributions</title>
      <p>Yuenan Wang: Writing—original draft; Tianxiao Jiang: Methodology; Tong Zhai: Formal analysis; Hongbin Liu: Project administration, Writing—review &amp; editing; All authors read and approved the final manuscript.</p>
    </sec>
    <sec id="sec6">
      <title>Data Availability Statement</title>
      <p>The original contributions presented in the study are included in the article, further inquiries can be directed to the corresponding author.</p>
    </sec>
  </body>
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