ソーシャルグラフとEdgeRank

Jun 19, 20107 likes1,505 views

The document discusses EdgeRank, an algorithm used by Facebook to determine what posts users see in their News Feed. It also discusses how EdgeRank could be applied to Twitter to help determine what tweets users see first. Several ideas are proposed for how EdgeRank might work on Twitter, including giving more weight to retweets, replies, favorites, and interactions with a user's social connections. An example implementation with a database to track this social graph data and rank tweets is briefly described.

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The document discusses changes to Facebook's Edgerank algorithm and provides recommendations for brands responding to those changes. Key points: - Edgerank now considers four factors: affinity, post type, time, and negative feedback. Engagement improves your score while time decay and negative feedback reduce it. - Reach for brand posts has decreased significantly according to some studies, though Facebook denies this. Engagement per fan reached has increased due to a more efficient algorithm. - To improve visibility, brands should focus on creating engaging content like questions, fill-in-the-blank posts, humor and memes rather than just sharing links. Leveraging trends and being controversial can also help. - While short

Modulo 2° Edge Rank ª Facebook [ Jesus Urzua ]Antonio Pascual Tacea

El documento explica el algoritmo Edgerank de Facebook, el cual determina qué publicaciones aparecen en los feeds de noticias de los usuarios. Edgerank asigna puntajes a cada publicación basado en factores como afinidad entre el usuario y el creador del contenido, tipo de interacción, y antigüedad de la publicación. El algoritmo es secreto y cambia constantemente para mejorar la experiencia del usuario en la plataforma.

Edge rankBim PRcom

The document discusses EdgeRank, which is Facebook's algorithm that determines what stories appear in a user's newsfeed. It notes that only 0.2% of potential stories are shown and that most users do not see status updates. It asks if users should care about optimizing for EdgeRank and suggests ways to do so, such as writing posts that encourage likes and comments from fans to increase engagement and impact the EdgeRank score.

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1. The document discusses the history of social media and technology from 1500 to present day. Key topics and companies discussed include Intel CPUs, Yahoo, Google, Facebook, Twitter, smartphones, and more. 2. It then focuses on specific social networks and technologies like Facebook EdgeRank, which determines ranking of posts in the News Feed, and Affinity Weight, which calculates a user's affinity for other accounts and content. 3. The document also examines search capabilities on Facebook and how they differ from traditional search engines like Google. It provides examples of search results from each.

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