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<article article-type="research-article" dtd-version="1.3" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xml:lang="en"><front><journal-meta><journal-id journal-id-type="publisher-id">gesj</journal-id><journal-title-group><journal-title xml:lang="en">GEOGRAPHY, ENVIRONMENT, SUSTAINABILITY</journal-title><trans-title-group xml:lang="ru"><trans-title>GEOGRAPHY, ENVIRONMENT, SUSTAINABILITY</trans-title></trans-title-group></journal-title-group><issn pub-type="ppub">2071-9388</issn><issn pub-type="epub">2542-1565</issn><publisher><publisher-name>Russian Geographical Society</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.24057/2071-9388-2022-107</article-id><article-id custom-type="elpub" pub-id-type="custom">gesj-2832</article-id><article-categories><subj-group subj-group-type="heading"><subject>Research Article</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="en"><subject>RESEARCH PAPER</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="ru"><subject>Статьи</subject></subj-group></article-categories><title-group><article-title>Regional Patterns Of Third-Level Digital Inequality In Russia: An Analysis Of Google Trends Data</article-title><trans-title-group xml:lang="ru"><trans-title></trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author" corresp="yes"><name-alternatives><name name-style="western" xml:lang="en"><surname>Chereshnia</surname><given-names>O. Yu.</given-names></name></name-alternatives><bio xml:lang="en"><p>Leninskie Gory, 1, Moscow, 119991</p></bio><email xlink:type="simple">chereshnia.o@geogr.msu.ru</email><xref ref-type="aff" rid="aff-1"/></contrib><contrib contrib-type="author" corresp="yes"><name-alternatives><name name-style="western" xml:lang="en"><surname>Gribok</surname><given-names>M. V.</given-names></name></name-alternatives><bio xml:lang="en"><p>Leninskie Gory, 1, Moscow, 119991</p></bio><xref ref-type="aff" rid="aff-1"/></contrib></contrib-group><aff xml:lang="en" id="aff-1"><institution>Lomonosov Moscow State University, Faculty of Geography</institution><country>Russian Federation</country></aff><pub-date pub-type="collection"><year>2023</year></pub-date><pub-date pub-type="epub"><day>07</day><month>04</month><year>2023</year></pub-date><volume>16</volume><issue>1</issue><fpage>26</fpage><lpage>35</lpage><permissions><copyright-statement>Copyright &amp;#x00A9; Chereshnia O.Y., Gribok M.V., 2023</copyright-statement><copyright-year>2023</copyright-year><copyright-holder xml:lang="ru">Chereshnia O.Y., Gribok M.V.</copyright-holder><copyright-holder xml:lang="en">Chereshnia O.Y., Gribok M.V.</copyright-holder><license xml:lang="ru" license-type="creative-commons-attribution" xlink:href="https://creativecommons.org/licenses/by/4.0/" xlink:type="simple"><license-p>Данная работа распространяется под лицензией Creative Commons Attribution 4.0.</license-p></license><license xml:lang="en" license-type="creative-commons-attribution" xlink:href="https://creativecommons.org/licenses/by/4.0/" xlink:type="simple"><license-p>This work is licensed under a Creative Commons Attribution 4.0 License.</license-p></license></permissions><self-uri xlink:href="https://ges.rgo.ru/jour/article/view/2832">https://ges.rgo.ru/jour/article/view/2832</self-uri><abstract><p>Digital inequality extends beyond mere access to technology. This study explores the concept of third-level digital inequality, which describes the situation where individuals or communities have access to technology and the Internet, have required skills, but still struggle to use it effectively. However, there is currently a lack of data and methods for assessing thirdlevel digital inequality. To address this gap, this study aimed to evaluate it on a regional scale by analyzing the popularity of Google search queries. In proposed method, the data are categorized into three groups: everyday services, education, science, and technology, and entertainment. On this basis authors calculated the index of Internet usage efficiency. The study’s findings revealed the territorial patterns of digital inequality in the constituent entities of the Russian Federation. Regions in North Caucasus and Siberia showed low Internet usage efficiency, while regions in the Urals and Central Russia had high Internet usage efficiency. The study’s methodology is quick, cost-effective, and easy to implement, but it also has limitations. The method only considers the popularity of certain search queries and does not consider the frequency or duration of internet usage, or the specific websites or services accessed, and does not consider individual-level factors that may influence internet usage patterns. The authors emphasize the importance of addressing not only differences in Internet access but also the lack of technology skills, digital literacy, and motivation among certain groups. 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