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  <doi_batch_id>aspg-31-1219-1791686984</doi_batch_id>
  <timestamp>20261011024944</timestamp>
  <depositor>
   <depositor_name>American Scientific Publishing Group</depositor_name>
   <email_address>admin@americaspg.com</email_address>
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  <registrant>American Scientific Publishing Group</registrant>
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  <journal>
   <journal_metadata language="en">
    <full_title>International Journal of Advances in Applied Computational Intelligence</full_title>
    <abbrev_title>IJAACI</abbrev_title>
    <issn media_type="electronic">2833-5600</issn>
   </journal_metadata>
   <journal_issue>
    <publication_date media_type="online">
     <year>2022</year>
    </publication_date>
    <journal_volume>
     <volume>1</volume>
    </journal_volume>
    <issue>1</issue>
   </journal_issue>
   <journal_article publication_type="full_text">
    <titles>
     <title>Natural Language Generation and Creative Writing A Systematic Review</title>
    </titles>
    <contributors>
     <person_name sequence="first" contributor_role="author">
      <given_name>Abdulla</given_name>
      <surname>Alsharhan</surname>
      <affiliations>
       <institution>
        <institution_name>Faculty of Engineering &amp; IT, The British University in Dubai, United Arab Emirates</institution_name>
       </institution>
      </affiliations>
     </person_name>
    </contributors>
    <jats:abstract>
     <jats:p>Among studies on natural language generation (NLG), computational creativity, and human-computer interaction; there is a vision of witnessing these tools collaborating with humans in generating and authoring creative content. This study aims to systematically review published studies discussing creative writing and story generation during the period of 2016-2021. This work seeks to identify the primary research methods used in NLG and creative writing studies, to locate how these studies are distributed geographically, and finally, to classify the subfields or common keywords primarily used in NLG involving creative writing. The findings suggest that experiment studies and problem-solving were the most common research methods in NLG and creative writing. Major identified themes in the reviewed articles include story generation, language models, and co-creativity, along with some gaps in foreign language translation and humour generation studies. The majority of the studies suggest that NLG tasks had a positive impact on creative writing. Common tasks related to NLG and creative writing are typically using keywords such as story generation, co-creativity, co-writing, user interface and writing tools. In future work, we aim to explore more GPT-3 capabilities in creative writing, in addition to creative writing applications in foreign language translation tasks.</jats:p>
    </jats:abstract>
    <publication_date media_type="online">
     <year>2022</year>
    </publication_date>
    <pages>
     <first_page>69</first_page>
     <last_page>90</last_page>
    </pages>
    <publisher_item>
     <item_number item_number_type="article-number">1219</item_number>
    </publisher_item>
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     <ai:license_ref applies_to="vor">https://creativecommons.org/licenses/by/4.0/</ai:license_ref>
    </ai:program>
    <doi_data>
     <doi>10.54216/IJAACI.010105</doi>
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