Tip: here are the keyword queries that people search for but don't actually find in the search results.
@evernote is a note-taking app which has #synchronization of notes across the different devices, it also works on #ipad #surface_pro and has #hashtags and #notebooks as well as a pretty good #search and #recommendation algorithm https://evernote.com/
@simplenote is a pretty simple minimalistic note-taking tool. it has #synchronization across the different devices and #hashtags and also supports #markdown which evernote doesn't https://simplenote.com/
@notion can almost function like #cms it has extended note #design features, it supports #media embed on the granular level, it works better than most note-taking apps with #data and #tables. It also has a good #organization mechanism for notes and supports #markdown https://notion.so
@roam_research is a note-taking tool, which main advantage is the capacity to make #connections between the notes using #markdown references. It also has a #search and #visualization function and operates using #bullet_points and #lists https://roamresearch.com/
@obsidian is a note-taking app that has support for #markdown and #connections between the different notes. It also has support for #synchronization and has a #visualization module https://obsidian.md/
@zettelkasten is more of a note-taking method, but it also has the software called the @archive. it supports #markdown and #connections between the notes as well as various #organization strategies and #hashtags.
@devonthink is a note-taking app that has #notebooks and can be good for #knowledge_management. it is also pretty good in #pdf storage and can be used to make notes with various research projects https://www.devontechnologies.com/apps/devonthink
The topics are the nodes (words) that tend to co-occur together in the same context (next to each other).
We use a combination of clustering and graph community detection algorithm (Blondel et al based on Louvain) to identify the groups of nodes are more densely connected together than with the rest of the network. They are aligned closer to each other on the graph and are given a distinct color.
We use the Jenks elbow cutoff algorithm to select the top prominent nodes that have significantly higher influence than the rest.
Click the Reveal Non-obvious button to remove the most influential words (or the ones you select) from the graph, to see what terms are hiding behind them.
The most influential nodes are either the ones with the highest betweenness centrality — appearing most often on the shortest path between any two randomly chosen nodes (i.e. linking the different distinct communities) — or the ones with the highest degree.
A structural gap shows the two distinct communities (clusters of words) in this graph that are important, but not yet connected. That's where the new potential and innovative ideas may reside.
This measure is based on a combination of the graph's connectivity and community structure, selecting the groups of nodes that would either make the graph more connected if it's too dispersed or that would help maintain diversity if it's too connected.
These are the latent brokers between the topics: the nodes that have an unusually high rate of influence (betweenness centrality) to their freqency — meaning they may appear not as often as the most influential nodes but they are important narrative shifting points.
These are usually brokers between different clusters / communities of nodes, playing not easily noticed and yet important role in this network, like the "grey cardinals" of sorts.