Asset Details
Do you wish to reserve the book?
SEO as Audience Analysis: Accounting for Algorithms in Content Strategy
Hey, we have placed the reservation for you!
By the way, why not check out events that you can attend while you pick your title.
Oops! Something went wrong.
Looks like we were not able to place the reservation. Kindly try again later.
Are you sure you want to remove the book from the shelf?
SEO as Audience Analysis: Accounting for Algorithms in Content Strategy
Do you wish to request the book?
SEO as Audience Analysis: Accounting for Algorithms in Content Strategy
Please be aware that the book you have requested cannot be checked out. If you would like to checkout this book, you can reserve another copy
We have requested the book for you!
Your request is successful and it will be processed during the Library working hours. Please check the status of your request in My Requests.
Oops! Something went wrong.
Looks like we were not able to place your request. Kindly try again later.
Journal Article
SEO as Audience Analysis: Accounting for Algorithms in Content Strategy
2024
Overview
Purpose: This project contributes a rhetorical approach to search engine optimization (SEO) as algorithmic audience analysis. It positions SEO as an activity that requires strategists to compose website content that is optimized to both human search engine users and the algorithmic
audience (Gallagher, 2017) of a search engine???s indexed content. Method: Actor-Network Theory (Latour, 2005), with its focus on the agency of non-human entities combined with human agency in social activity, provides the theoretical framework for this approach. The project combines
usability testing with web development methods to trace rhetorical agency during online search activities (Hocutt, 2019). Doing so demonstrates the role search algorithms play as receptive audiences of SEO strategies. Results: Approaches to teaching SEO within the framework of technical
and professional communication (TPC) rhetorical foundations require understanding the algorithmic audiences of SEO practices. By matching timestamp data from videorecorded usability tests and HTTP archive (HAR) files produced during usability testing sessions, content strategists can overlay
the chronological recordings with their SEO strategies to better understand how successfully SEO met human and algorithmic audience expectations. When SEO practice identifies human audience expectations effectively and develops content signals attractive to its technological audiences, both
audiences succeed in an assembled meaning-making exercise. By applying existing methods of audience analysis to search algorithms, content strategists can improve SEO and help surface relevant content for their human users. Conclusion: The results of this project provide a framework
for practicing SEO as rhetorical activity built upon audience analysis of both human and non-human users.
Publisher
Society for Technical Communication
Subject
