Linguistic insights into high-quality content for SEO: Optimizing high-quality content with Grice's conversational maxims
•Search engine optimization improves a website's visibility and targeted traffic.•Linguistics adds new insights to content creation and optimization.•Conversational maxims can enhance content quality for higher search rankings. Attaining a first-page position in search engine results is crucial...
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Veröffentlicht in: | Telematics and Informatics Reports 2024-12, Vol.16, p.100169, Article 100169 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | •Search engine optimization improves a website's visibility and targeted traffic.•Linguistics adds new insights to content creation and optimization.•Conversational maxims can enhance content quality for higher search rankings.
Attaining a first-page position in search engine results is crucial for websites, impacting their visibility. Search engine optimization involves technical and content optimization strategies to enhance a website's visibility. Central to this effort is the creation and maintenance of high-quality content that satisfies search engine algorithms and engages the intended audience. However, creating high-quality content is inherently challenging due to its subjective and multifaceted nature. This study addresses this challenge by analyzing high-quality content through a linguistic lens. It introduces a tailored framework that includes textual, stylistic, technical, and regulatory criteria, outlining the essential features of user-oriented high-quality content. Furthermore, this research advocates for the application of Grice's conversational maxims—quality, quantity, relevance, and manner—in content creation and optimization to enhance the development of high-quality content. Employing a quantitative methodology and drawing on findings from an experiment conducted on Google's search engine platform, this study promotes the effective utilization of these maxims to cultivate high-quality content and improve rankings on search engine results pages. |
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ISSN: | 2772-5030 2772-5030 |
DOI: | 10.1016/j.teler.2024.100169 |