SharkFest’25 US is right around the corner — kicking off June 14 in Richmond, VA!

Join #Wireshark users, instructors, and core developers for hands-on learning, expert sessions, and deep dives into packet analysis, protocol troubleshooting, and tools like #Stratoshark. Whether you're new to Wireshark or a seasoned pro, this is the event for leveling up your network skills.

Don’t miss it — register now: https://sharkfest.wireshark.org/sfus
#sf25us #NetworkAnalysis #PacketAnalysis

Ever wondered what hidden gems lie within your network traffic? My latest article in the #100sSeries dives into extracting secrets using Wireshark Read more: https://osintteam.blog/wireshark-101-extracting-secrets-from-captured-network-data-8f40bd3252f9 #Wireshark #NetworkAnalysis #CyberSecurity #InfoSec

Using knowledge graphs for network correspondence analyses, a Finnish case study using their national Sampo-infrastructure as triple-store and SPARQL endpoint.

I now released the tabular data of my network analysis (part of my PhD): Experts and Auctioneers in Paris Art Auctions 1852-1862

Description: https://doi.org/10.17613/M60Z96

Chapter in "Das Spektakel der Auktion" (2020): https://books.openedition.org/editionsmsh/23978

Data: https://doi.org/10.14279/depositonce-22602

The Hidden Networks
That Rule Our World
S2 E50

Join us for a fascinating deep dive into the world of network analysis, where we explore Node2Vec - a groundbreaking algorithm that helps us understand the hidden communities within complex networks. Unlock profound insights about communities hidden within the vast connections surrounding us.

https://helioxpodcast.substack.com/p/the-hidden-networks-that-rule-our

#NetworkAnalysis #AI #ComplexSystems #GraphTheory #Node2Vec #NeuralNetworks #SocialNetworks #Podcast

https://www.buzzsprout.com/2405788/episodes/16420355

How can digital methods help to provide new insights into the power & cooperation dynamics of the Yuan Dynasty?

This week in our #DigitalHistoryOFK, Wonhee Cho (Yonsei University, South Korea) will discuss how “cooperation #NetworkAnalysis” can be used to examine the relationships between officials at the Yuan court to gain insights into the roles of Han and non-Han elites under Mongol rule.

11 Dec, 4–6 pm (CET), online
Info: https://dhistory.hypotheses.org/9083

I don't do a lot of #NetworkAnalysis in my work, but there are many in @digigeolab who do, and presumably here as well.

I know #NetworkX is a commonly used Python library for such analysis, but it is a bit slow. However, there is a new spin of it called #RustworkX written in Rust, which makes it blisteringly fast.

Here are some benchmarks: https://www.rustworkx.org/dev/benchmarks.html

Has anyone tried it? Any opinions?

Golnaz Sarkar Farshi just announced the release of MLNA, a Python package and app for MultiLingual Network Analysis

MLNA official website: https://goli-sf.github.io/MLNA/
Video tutorials:
* For Python Users: To learn how to use MLNA in a Python script, watch this tutorial: https://youtu.be/FuPgneZ5wGU
* For Non-Programmers: To discover how to utilize the MLNA app, watch this tutorial: https://youtu.be/3c1C4b4D9BI.

Feedback is welcome: golnaz.sarkarfarshi@uni-marburg.de

Is there currently a kind of comparison portal for #networkanalysis tools, with an overview of which programme is best suited for which action? I need to give an introduction on this and am particularly familiar with Gephi. But there seems to be a lot in favour of NodeXL - or Nodegoat? Is Pajek still in use?

We are looking for #Mastodon accounts across instances to follow ...

We are interested in all things #DH; #DSE / #SDE; #TEI, #Python, #Git; #NetworkAnalysis; 20th-century #poetry; #correspondence; #QueerHistory; and, well, #WHAuden.

If you can point out to us relevant accounts, we will be very thankful!

I thought I remembered someone here was working on a library to create and analyse #hypergraphs (potentially in #rust but I'm not sure).

Does anyone know who that might be? I wanted to check the library but I haven't been able to find it (or if I have, I did not recognize it).

Basically, anyone working on a hypergraph library, please ping me

This item has been nine years on my to-do list

I've just released a dataset made of character networks based on the 20 novels composing Zola's Les Rougon-Macquart.

Data and more details here: https://github.com/yrochat/Zola-Character-Network-Dataset/

Hooray! I'm free!

hey #datascience nerds: can I just gush for a second on how great the combination of #ZFS and #LMDB is?

I'm working with a 2.1 TB LMDB database of academic citations. I have half a dozen processes hammering away at this at random. But between ZFS's compression and excellent caching and LMDB's clever use of caching I'm barely hitting the disk at all (99% cache hit rate), and it's only using about 15GB memory.

Meine Monographie „Wiener Ansichten zur Kunst der Avantgarde. Geschichte, Netzwerk und Diskurs der Kunstkritik zu Beginn des 20. Jahrhunderts“, welche 2020 im Verlag new academic press (nap) erschienen ist, ist seit heute #openaccess über die Publikationsplattform ART DOK der Universitätsbibliothek Heidelberg verfügbar.
Link >> http://archiv.ub.uni-heidelberg.de/artdok/volltexte/2024/9087

Sunday inspiration:

In this multi-authored essay, thirteen participants in the Getty Advanced Workshop on Network Analysis + Digital Art History (NA+DAH) share their experiences. They discuss learning and working at the intersection of these fields, offering insights into their community-building efforts.
#DigitalArtHistory #NetworkAnalysis #GettyWorkshop #AcademicResearch #InterdisciplinaryStudies #CommunityBuilding
https://dahj.org/article/network-analysis

Interested in the history of art around 1900 and artists’ networks? You can now read my paper “The ‘Who's Who?’ of Künstlerhaus Exhibitors A Guide to Analyze Entangled Artists Biographies Based on Wikidata” on reserchgate by following the subsequent link .
Link to the paper https://www.researchgate.net/publication/379664717_The_Who%27s_Who_of_Kunstlerhaus_Exhibitors_A_Guide_to_Analyze_Entangled_Artists_Biographies_Based_on_Wikidata
Link to the dataset and interactive visualization https://github.com/m-kaiser/Kuenstlerhaus-Wien-Network
#wikidata #networkanalysis #19thcentury #arthistory #openscience

Interesting graph-based visualization
https://fedihum.org/@johlei/112123502764576627