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<ArticleSet>
  <Article>
    <Journal>
      <PublisherName>IJIRCSTJournal</PublisherName>
      <JournalTitle>International Journal of Innovative Research in Computer Science and Technology</JournalTitle>
      <PISSN>I</PISSN>
      <EISSN>S</EISSN>
      <Volume-Issue>Volume 11 Issue 3</Volume-Issue>
      <PartNumber/>
      <IssueTopic>Computer Science &amp; Engineering</IssueTopic>
      <IssueLanguage>English</IssueLanguage>
      <Season>May - June 2023</Season>
      <SpecialIssue>N</SpecialIssue>
      <SupplementaryIssue>N</SupplementaryIssue>
      <IssueOA>Y</IssueOA>
      <PubDate>
        <Year>2023</Year>
        <Month>09</Month>
        <Day>07</Day>
      </PubDate>
      <ArticleType>Computer Sciences</ArticleType>
      <ArticleTitle>Digital Marketing Analysis on Social Media Using Machine Learning</ArticleTitle>
      <SubTitle/>
      <ArticleLanguage>English</ArticleLanguage>
      <ArticleOA>Y</ArticleOA>
      <FirstPage>101</FirstPage>
      <LastPage>104</LastPage>
      <AuthorList>
        <Author>
          <FirstName>A.Mounika</FirstName>          
          <AuthorLanguage>English</AuthorLanguage>
          <Affiliation/>
          <CorrespondingAuthor>Y</CorrespondingAuthor>
          <ORCID/>
                      <FirstName>T.Venkata Naga Jayanth</FirstName>          
          <AuthorLanguage>English</AuthorLanguage>
          <Affiliation/>
          <CorrespondingAuthor>N</CorrespondingAuthor>
          <ORCID/>
                    <FirstName>M.Venkata Vishnu Vardhan</FirstName>          
          <AuthorLanguage>English</AuthorLanguage>
          <Affiliation/>
          <CorrespondingAuthor>N</CorrespondingAuthor>
          <ORCID/>
                    <FirstName>S.SaiVenkata Bharadwaj</FirstName>          
          <AuthorLanguage>English</AuthorLanguage>
          <Affiliation/>
          <CorrespondingAuthor>N</CorrespondingAuthor>
          <ORCID/>
                    <FirstName>M.Shalim Raj</FirstName>          
          <AuthorLanguage>English</AuthorLanguage>
          <Affiliation/>
          <CorrespondingAuthor>N</CorrespondingAuthor>
          <ORCID/>
           
        </Author>
      </AuthorList>
      <DOI>https://doi.org/10.55524/ijircst.2023.11.3.20</DOI>
      <Abstract>The field of machine learning has received insufficient attention. Because of their superior Artificial Intelligence, machines that are capable of deep learning have the potential to push the boundaries of what is possible in digital marketing. This study intends to uncover the outcomes from the study of Indian customers&amp;#39; responses across a variety of demographics to machines and their capacities to sell, which may very well be the future of digital marketing. We have found that software developers need to construct the architecture in conjunction with digital marketers. These digital marketers utilize machines with deep learning to take into consideration the attitudes of customers as well as their behaviors and choices. As a result, in the not-too-distant future, marketers will have convenient access to correct information regarding clients, which will unlock enormous benefits for the companies. A causal model that makes use of regression models is used to explain how the performance of the machines is likely to change depending on the circumstances. SPSS version 24 and R software were used for the analysis of the data. Data regarding the customer&amp;#39;s behaviors, their choices, and emotions are collected, and fuzzy-set qualitative comparative analysis (fsQCA) approach is used to determine how they can be influenced to use the services of the machine.</Abstract>
      <AbstractLanguage>English</AbstractLanguage>
      <Keywords>Machine Learning, Digital Marketing, Social Media, Fuzzy Set</Keywords>
      <URLs>
        <Abstract>https://ijircst.org/abstract.php?article_id=1173</Abstract>
      </URLs>      
    </Journal>
  </Article>
</ArticleSet>