Luca Hammer ENNetwork visualization: Mastodon Instances - Hashtags
- 2 284 #Mastodon instances from https://fediverse.network/mastodon
- 2 000 public Toots (API) per instance
- Hashtags of those Toots
Core of the hashtag network. Instances are white with fixed size, hashtags colored and size by number of uses.
Most used #hashtags in the collected Toots:
#mastodon 2 825
#nowplaying 2 130
#drawing 1733
#qanon 1356
#気象警報注意報 1283
#vape 1154
#vegan 1067
#funkwhale 966
#introductions 785
#openstreetmap 760
#電子タバコ 753
#photography 722
#fediverse 618
Interactive Mastodon Hashtag Network: https://lucahammer.at/vis/fediverse/2018-08-29-mastoverse_hashtags/
You can search for hashtags and instances.
Clicking on a #hashtag shows the instances it was recently used on.
Clicking on a instance shows the hashtags that were recently used there.
I am investigating why there are instances missing. Could be a problem with data collection or export.
I found some problems in yesterdays data. Primarily caused by a bug in the code (same Toots were collected over and over). I updated the Gist with the fixed code. https://gist.github.com/lucahammer/8e31fa100446c3b7c783a00bd006003a
For todays run I used my own list of #mastodon instances which I collected for the #fediverse visualization: https://vis.social/@Luca/100606625507856187
Python script to generate a GDF for Gephi to visualize the Mastodon Hashtag Network https://vis.social/web/statuses/100634263439065513
Python script to generate a GDF for Gephi to visualize the Mastodon Hashtag Network https://vis.social/web/statuses/100634263439065513 - mastodon-hashtag-network.py
- 761 of 2044 instances responded (api/v1/timelines/public?local=true)
- Up to 4k Toots per instance
- 231 510 #hashtags
- 42 900 different hashtags
- Up to 4k Toots per instance
- 231 510 #hashtags
- 42 900 different hashtags
Most used #tags
#stockings 2724
#朝日新聞デジタル 2599
#社会 2135
#気象警報注意報 2061
#mlp 1894
#mastodon 1759
#writing 1451
#trump 1303
#brony 1252
#mylittlepony 1217
#auxerre 1166
#blog 1144
#kentoazumi 1119
#muenchen 1108
#tech 1082
#introduction 1077
#fairmuenchen 1070
#comic 1033
#hackernews 1001
#photography 993
#mlpcomic 984
#fancomic 984
#introductions 961
#unitedstatespoliticsandgovernment 951
#明石市 933
#nowplaying 896
#photo 873
#ironème 822
#lewd 813
#気象情報 788
#しんぶん赤旗 776
#cats 762
#linux 664
#art 650
#stockings 2724
#朝日新聞デジタル 2599
#社会 2135
#気象警報注意報 2061
#mlp 1894
#mastodon 1759
#writing 1451
#trump 1303
#brony 1252
#mylittlepony 1217
#auxerre 1166
#blog 1144
#kentoazumi 1119
#muenchen 1108
#tech 1082
#introduction 1077
#fairmuenchen 1070
#comic 1033
#hackernews 1001
#photography 993
#mlpcomic 984
#fancomic 984
#introductions 961
#unitedstatespoliticsandgovernment 951
#明石市 933
#nowplaying 896
#photo 873
#ironème 822
#lewd 813
#気象情報 788
#しんぶん赤旗 776
#cats 762
#linux 664
#art 650
#Hashtags used by most instances:
#mastodon 204
#introductions 171
#introduction 132
#linux 104
#music 96
#nowplaying 92
#art 83
#fediverse 82
#twitter 73
#android 72
#privacy 67
#facebook 66
#peertube 61
#opensource 59
#ff 55
#google 54
#security 54
#youtube 53
#cats 52
#firefox 50
#gaming 50
#python 50
#np 50
#gdpr 48
#foss 48
#javascript 47
#photography 47
#programming 45
#cat 45
#ubuntu 45
#mastoart 44
#history 44
#podcast 43
#science 43
#books 41
#activitypub 40
#github 40
Instances highest hashtag density:
https://route66.social 17922
https://unnerv.jp 8532
https://equestria.social 8513
https://social.homunyan.com 7566
https://s2.libera.blue 6989
https://assortedflotsam.com 5622
https://www.frei.social 5574
https://frei.social 5574
https://mastodon.dc919.org 4627
https://diaspodon.fr 4468
https://akashiensis.com 4393
https://photog.social 4238
https://bonn.social 3634
https://s10y.eu 3597
https://qoto.org 3563
https://baraag.net 3384
Instances by most diverse hashtag usage:
https://route66.social 3233
https://bonn.social 1672
https://s10y.eu 1669
https://assortedflotsam.com 1664
https://social.tchncs.de 1561
https://diaspodon.fr 1521
https://social.coop 1323
https://toot.chat 1059
https://baraag.net 1058
https://fosstodon.org 1058
https://mastodon.technology 1003
https://occitanie.social 986
https://mastodon.social 985
https://sunbeam.city 943
https://photog.social 926
https://www.frei.social 899
Updated version of the Interactive
Mastodon Hashtag Network.
Warning: 10MB. Desktop computer recommended.
https://lucahammer.at/vis/fediverse/2018-08-30-mastoverse_hashtags/
Zach moved to new instance@Luca Used this to explore hashtag usage and find someone to follow on another instance I never would have encountered otherwise. 👍
codesectionsVery cool!
When you select an instance and get the Information Pane on the right, what's the sort order for the hashtags listed under "connections"? It doesn't appear to be the most commonly used hashtags
@codesections To be honest: I don't know. I used the default sigmaJS Exporter in Gephi and only tweaked some settings.
Thanks. Another question: what do the colors of the lines mean?
@codesections They indicate clusters. Calculated by the Modularity algorithm. Because of the mixed nodes, not very meaningful.
Ondřej PokornýYou can use http://www.unmung.com/mastoview?url=s10y.eu&view=local to preview local timelines. I hope that it will some day possible to visit/pin them from within tootsuite and other clients.
diogo@Luca
you can pin a instance with the mastalab app, available for android
you can pin a instance with the mastalab app, available for android
Luca Hammer EN (@[email protected])
1.02K Posts, 1.63K Following, 6.78K Followers · Scientific programmer @[email protected] at University of Siegen. Neurodivergent. Helped thousands of people migrate their social graph to the Fediverse with #fedifinder. This account focuses on my work and projects. For everything else, follow @[email protected]. #SocialMedia #Python #Gephi #Data #MediaStudies #fedi22
@Luca
Well I guess a few bots and a few fetishists can really impact these top stats.
Well I guess a few bots and a few fetishists can really impact these top stats.