Book contents
- Frontmatter
- Contents
- Acknowledgements
- one Introduction: Unpicking the Automation of Memory Making
- two A Taxonomy of Memory Themes: Partitioning the Memorable
- three The Computational Surfacing of Memories: Promoting the Memorable
- four The Reception of Targeted Memories in Everyday Life: Classificatory Struggles and the Tensions of Remembering
- five Conclusion: Sorting the Past
- Notes
- References
- Index
three - The Computational Surfacing of Memories: Promoting the Memorable
Published online by Cambridge University Press: 04 January 2022
- Frontmatter
- Contents
- Acknowledgements
- one Introduction: Unpicking the Automation of Memory Making
- two A Taxonomy of Memory Themes: Partitioning the Memorable
- three The Computational Surfacing of Memories: Promoting the Memorable
- four The Reception of Targeted Memories in Everyday Life: Classificatory Struggles and the Tensions of Remembering
- five Conclusion: Sorting the Past
- Notes
- References
- Index
Summary
Although we are talking about the automated production of memory in this book, these systems are still anchored by classification systems that open them up to a much longer held and well-established, as Foucault (2002) put it, order of things. It is also important to note that ‘The Taxonomy of Memory Themes’ discussed in Chapter Two served as the ‘ground truth’ (Amoore, 2020), so to speak, for the development of Facebook Memories. Established prior to its development, the memory classifications generated by Facebook's research studies were fed into the design of Facebook's current throwback feature. This was effectively a moment in which the formalization of a computational problem occurred and where there was an attempt to render the indeterminable and contingent into something calculable (see Fazi, 2018). Once this taxonomy of memories was in place, it provided the ranking algorithms with a clear-cut computational problem to ‘solve’ and optimize: what to surface, to whom and when. In other words, once there was a system in place for classifying memories within the taxonomy, the system had to then decide which memory, from all these many classified memories, should be targeted at the intended recipient and when they should receive it. Once the classificatory system is active within this social media archive, the focus then has to shift to retrieval and to the way in which this retrieval is instantiated in processes of ranking. Bringing memories to the surface requires, in this logic, a system by which they can be ranked – memories ranked at a certain level are the ones that then become visible. It is this ranking of memory that this chapter deals with.
Feedback loops and the surfacing of memories
In a Facebook Research report titled ‘Engineering for nostalgia: building a personalized “On This Day” experience’, Manohar Paluri and Omid Aziz (2016) outline the software engineering side to building the earlier iteration of Facebook Memories called On This Day. The claim behind this, they explain, is that they ‘wanted to make sure On This Day shows people the memories they most likely want to see and share, especially when it comes to the memories they see in News Feed’ (Paluri & Aziz, 2016).
- Type
- Chapter
- Information
- Social Media and the Automatic Production of MemoryClassification, Ranking and the Sorting of the Past, pp. 43 - 56Publisher: Bristol University PressPrint publication year: 2021