Textual Patterns and Virality in X: An Analysis of Engagement in Telenovela Posts

<!DOCTYPE html> <html lang="en" xml:lang="en"> <head> <meta charset="utf-8"> <meta name="viewport" content="width=device-width, initial-scale=1.0"> <title> Textual Patterns and Virality in X: An Analysis of Engagement in Telenovela Posts | U.Porto Journal of Engineering </title> <link rel="icon" href="https://journalengineering.fe.up.pt/public/journals/3/favicon_en_US.png"> <meta name="generator" content="Open Journal Systems 3.4.0.3"> <link rel="schema.DC" href="http://purl.org/dc/elements/1.1/" /> <meta name="DC.Creator.PersonalName" content="William Ferreira"/> <meta name="DC.Creator.PersonalName" content="Jefferson Lima"/> <meta name="DC.Date.created" scheme="ISO8601" content="2024-07-16"/> <meta name="DC.Date.dateSubmitted" scheme="ISO8601" content="2024-04-16"/> <meta name="DC.Date.issued" scheme="ISO8601" content="2024-07-10"/> <meta name="DC.Date.modified" scheme="ISO8601" content="2024-07-31"/> <meta name="DC.Description" xml:lang="en" content="X, previously known as Twitter, boasts 556 million active users and is widely used by businesses to engage with their audiences. In our study, we focused on TV Globo's telenovela "Terra e Paix茫o" broadcast in 2023, to analyze the impact of textual patterns on post virality using natural language processing techniques. Techniques like sentiment analysis, Part-Of-Speech Tagging, reinforcement scoring, TF-IDF, semantic similarity, and cosine similarity were utilized to identify attributes that contribute to a post's success, aiming to enhance marketing strategies. We employed language models like BERT, RoBERTa, and e5 in our analysis. Our findings indicate that while various metrics affect post engagement, the challenge remains complex. Textual characteristics, although essential, do not fully explain a publication's popularity, underscoring the need for a multifaceted approach to understanding social media dynamics."/> <meta name="DC.Format" scheme="IMT" content="application/pdf"/> <meta name="DC.Identifier" content="2183-6493_0010-003_002630"/> <meta name="DC.Identifier.pageNumber" content="47-58"/> <meta name="DC.Identifier.DOI" content="10.24840/2183-6493_0010-003_002630"/> <meta name="DC.Identifier.URI" content="https://journalengineering.fe.up.pt/index.php/upjeng/article/view/2183-6493_0010-003_002630"/> <meta name="DC.Language" scheme="ISO639-1" content="en"/> <meta name="DC.Rights" content="Copyright (c) 2024 William S Ferreira; Jefferson Lima"/> <meta name="DC.Rights" content="https://creativecommons.org/licenses/by/4.0"/> <meta name="DC.Source" content="U.Porto Journal of Engineering"/> <meta name="DC.Source.ISSN" content="2183-6493"/> <meta name="DC.Source.Issue" content="3"/> <meta name="DC.Source.Volume" content="10"/> <meta name="DC.Source.URI" content="https://journalengineering.fe.up.pt/index.php/upjeng"/> <meta name="DC.Subject" xml:lang="en" content="Virality"/> <meta name="DC.Subject" xml:lang="en" content="Text Analysis"/> <meta name="DC.Subject" xml:lang="en" content="Natural Language Processing"/> <meta name="DC.Subject" xml:lang="en" content="Engagement"/> <meta name="DC.Subject" xml:lang="en" content="Social Media"/> <meta name="DC.Title" content="Textual Patterns and Virality in X: An Analysis of Engagement in Telenovela Posts"/> <meta name="DC.Type" content="Text.Serial.Journal"/> <meta name="DC.Type.articleType" content="PEC202324_02"/> <meta name="gs_meta_revision" content="1.1"/> <meta name="citation_journal_title" content="U.Porto Journal of Engineering"/> <meta name="citation_journal_abbrev" content="UPjeng"/> <meta name="citation_issn" content="2183-6493"/> <meta name="citation_author" content="William Ferreira"/> <meta name="citation_author_institution" content="University of Porto, Faculty of Engineering. "/> <meta name="citation_author" content="Jefferson Lima"/> <meta name="citation_author_institution" content="Federal University of Pernambuco, Informatics Center."/> <meta name="citation_title" content="Textual Patterns and Virality in X: An Analysis of Engagement in Telenovela Posts"/> <meta name="citation_language" content="en"/> <meta name="citation_date" content="2024/07/16"/> <meta name="citation_volume" content="10"/> <meta name="citation_issue" content="3"/> <meta name="citation_firstpage" content="47"/> <meta name="citation_lastpage" content="58"/> <meta name="citation_doi" content="10.24840/2183-6493_0010-003_002630"/> <meta name="citation_abstract_html_url" content="https://journalengineering.fe.up.pt/index.php/upjeng/article/view/2183-6493_0010-003_002630"/> <meta name="citation_abstract" xml:lang="en" content="X, previously known as Twitter, boasts 556 million active users and is widely used by businesses to engage with their audiences. In our study, we focused on TV Globo's telenovela "Terra e Paix茫o" broadcast in 2023, to analyze the impact of textual patterns on post virality using natural language processing techniques. Techniques like sentiment analysis, Part-Of-Speech Tagging, reinforcement scoring, TF-IDF, semantic similarity, and cosine similarity were utilized to identify attributes that contribute to a post's success, aiming to enhance marketing strategies. We employed language models like BERT, RoBERTa, and e5 in our analysis. Our findings indicate that while various metrics affect post engagement, the challenge remains complex. Textual characteristics, although essential, do not fully explain a publication's popularity, underscoring the need for a multifaceted approach to understanding social media dynamics."/> <meta name="citation_keywords" xml:lang="en" content="Virality"/> <meta name="citation_keywords" xml:lang="en" content="Text Analysis"/> <meta name="citation_keywords" xml:lang="en" content="Natural Language Processing"/> <meta name="citation_keywords" xml:lang="en" content="Engagement"/> <meta name="citation_keywords" xml:lang="en" content="Social Media"/> <meta name="citation_pdf_url" content="https://journalengineering.fe.up.pt/index.php/upjeng/article/download/2183-6493_0010-003_002630/865"/> <link rel="alternate" type="application/atom+xml" href="https://journalengineering.fe.up.pt/index.php/upjeng/gateway/plugin/APP%5Cplugins%5Cgeneric%5CwebFeed%5CWebFeedGatewayPlugin/atom"> <link rel="alternate" type="application/rdf+xml" href="https://journalengineering.fe.up.pt/index.php/upjeng/gateway/plugin/APP%5Cplugins%5Cgeneric%5CwebFeed%5CWebFeedGatewayPlugin/rss"> <link rel="alternate" type="application/rss+xml" href="https://journalengineering.fe.up.pt/index.php/upjeng/gateway/plugin/APP%5Cplugins%5Cgeneric%5CwebFeed%5CWebFeedGatewayPlugin/rss2"> <link rel="stylesheet" href="https://journalengineering.fe.up.pt/index.php/upjeng/$$$call$$$/page/page/css?name=bootstrap" type="text/css" /> </head> <body class="pkp_page_article pkp_op_view has_site_logo"> <div class="pkp_structure_page"> <nav id="accessibility-nav" class="sr-only" role="navigation" aria-label="Quick jump to page content"> <ul> <li><a href="#main-navigation">Main Navigation</a></li> <li><a href="#main-content">Main Content</a></li> <li><a href="#sidebar">Sidebar</a></li> </ul> </nav> <header class="navbar navbar-default" id="headerNavigationContainer" role="banner"> <div class="container-fluid"> <div class="row"> <nav aria-label="User Navigation"> <ul id="navigationUser" class="nav nav-pills tab-list pull-right"> <li class=" menu-item-1"> <a href="https://journalengineering.fe.up.pt/index.php/upjeng/user/register"> Register </a> </li> <li class=" menu-item-2"> <a href="https://journalengineering.fe.up.pt/index.php/upjeng/login"> Login </a> </li> </ul> </nav> </div> </div> <div class="container-fluid"> <div class="navbar-header"> <button type="button" class="navbar-toggle collapsed" data-toggle="collapse" data-target="#nav-menu" aria-expanded="false" aria-controls="nav-menu"> <span class="sr-only">Toggle navigation</span> <span class="icon-bar"></span> <span class="icon-bar"></span> <span class="icon-bar"></span> </button> <div class="site-name"> <a href=" https://journalengineering.fe.up.pt/index.php/upjeng/index " class="navbar-brand navbar-brand-logo"> <img src="https://journalengineering.fe.up.pt/public/journals/3/pageHeaderLogoImage_en_US.png" alt="U. 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In our study, we focused on TV Globo's telenovela "<em>Terra e Paix茫o</em>" broadcast in 2023, to analyze the impact of textual patterns on post virality using natural language processing techniques. Techniques like sentiment analysis, Part-Of-Speech Tagging, reinforcement scoring, TF-IDF, semantic similarity, and cosine similarity were utilized to identify attributes that contribute to a post's success, aiming to enhance marketing strategies. We employed language models like BERT, RoBERTa, and e5 in our analysis. Our findings indicate that while various metrics affect post engagement, the challenge remains complex. Textual characteristics, although essential, do not fully explain a publication's popularity, underscoring the need for a multifaceted approach to understanding social media dynamics.</p> </div> </div> <section class="item downloads_chart"> <h2 class="label"> Downloads </h2> <div class="value"> <canvas class="usageStatsGraph" data-object-type="Submission" data-object-id="2630"></canvas> <div class="usageStatsUnavailable" data-object-type="Submission" data-object-id="2630"> Download data is not yet available. </div> </div> </section> </section> <section class="article-more-details"> <h2 class="sr-only">Article Details</h2>   <div class="panel panel-default copyright"> <div class="panel-body"> <a rel="license" href="https://creativecommons.org/licenses/by/4.0/"><img alt="Creative Commons License" src="//i.creativecommons.org/l/by/4.0/88x31.png" /></a><p>This work is licensed under a <a rel="license" href="https://creativecommons.org/licenses/by/4.0/">Creative Commons Attribution 4.0 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Textual Patterns and Virality in X: An Analysis of Engagement in Telenovela Posts | U.Porto Journal of Engineering