Tootfinder

This https://arxiv.org/abs/2303.15702 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csDC_…

Distributed Graph Embedding with Information-Oriented Random Walks
Graph embedding maps graph nodes to low-dimensional vectors, and is widely adopted in machine learning tasks. The increasing availability of billion-edge graphs underscores the importance of learning efficient and effective embeddings on large graphs, such as link prediction on Twitter with over one billion edges. Most existing graph embedding methods fall short of reaching high data scalability. In this paper, we present a general-purpose, distributed, information-centric random walk-based gra…

Ooooops.

Overdue, but I’ve added the machinery to automatically add opengraph images to my blog entries #hugo
https://blog.lanzani.nl/2024/open-graph-hugo/

Automatically add images for Open Graph in Hugo · Technical inconsistencies blog
While using a static site generator is a low-maintenance endeavor, it also means that complex requirements need to be coded if nobody has done it before. Today, I automated image previews that can be used to display a nice preview through for Open Graph (and Twitter cards!). The Open Graph protocol enables any web page to become a rich object in a social graph. My blog, however, is text-heavy and often misses the images, so I had to come up with something else.

@… I landed OG imgs!
Seems best to stick to PNG and JPG OG images. https://www.opengraph.xyz/blog/the-ultimate-guide-to-open-g…

Open Graph Image Guide: Boost Engagement & Clicks on Social Media
Unlock the secrets of Open Graph images to elevate your content's social media impact. Learn to create, design, and implement compelling Open Graph tags for better engagement, visibility, and click-through rates on platforms like Facebook, Twitter, and LinkedIn. Essential reading for digital marketers, bloggers, and content creators.

Ooooops.

Another BMI (Big #Mastodon Influx) kicking off. What did the manbaby say/do this time?
#ElonMusk #Twitter

Temporal Analysis of Drifting Hashtags in Textual Data Streams: A Graph-Based Application
Cristiano M. Garcia, Alceu de Souza Britto Jr, Jean Paul Barddal
https://arxiv.org/abs/2402.10230

Temporal Analysis of Drifting Hashtags in Textual Data Streams: A Graph-Based Application
Social media has played an important role since its emergence. People use the internet to express opinions about anything, making social media platforms a social sensor. Initially supported by Twitter, the hashtags are now in use on several social media platforms. Hashtags are helpful to tag, track, and group posts on similar topics. In this paper, we analyze hashtag drifts over time using concepts from graph analysis and textual data streams using the Girvan-Newman method to uncover hashtag co…

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Link Recommendation to Augment Influence Diffusion with Provable Guarantees
Xiaolong Chen, Yifan Song, Jing Tang
https://arxiv.org/abs/2402.19189 https://<…

Link Recommendation to Augment Influence Diffusion with Provable Guarantees
Link recommendation systems in online social networks (OSNs), such as Facebook's ``People You May Know'', Twitter's ``Who to Follow'', and Instagram's ``Suggested Accounts'', facilitate the formation of new connections among users. This paper addresses the challenge of link recommendation for the purpose of social influence maximization. In particular, given a graph $G$ and the seed set $S$, our objective is to select $k$ edges that connect seed nodes and ordinary nodes to optimize the influenc…