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https://github.com/pmonks/fake-tweets
Fake tweets generated by a Markov chain built from a Twitter archive
https://github.com/pmonks/fake-tweets
clojure markov-chain tweets twitter
Last synced: 9 days ago
JSON representation
Fake tweets generated by a Markov chain built from a Twitter archive
- Host: GitHub
- URL: https://github.com/pmonks/fake-tweets
- Owner: pmonks
- License: other
- Created: 2020-04-29T06:37:25.000Z (over 4 years ago)
- Default Branch: main
- Last Pushed: 2024-01-17T18:59:47.000Z (10 months ago)
- Last Synced: 2024-10-15T15:19:18.535Z (21 days ago)
- Topics: clojure, markov-chain, tweets, twitter
- Language: Clojure
- Homepage:
- Size: 92.8 KB
- Stars: 5
- Watchers: 3
- Forks: 2
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
- Contributing: .github/CONTRIBUTING.md
- License: LICENSE
- Code of conduct: .github/CODE_OF_CONDUCT.md
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# fake-tweets
A small library that builds a Markov chain from a tweet archive in JSON format, then spits out any number of statistically similar, though fake, tweets.
## Trying it Out
### Providing a JSON Archive
Download a JSON tweet archive, for example via [Twitter's export function](https://help.twitter.com/en/managing-your-account/how-to-download-your-twitter-archive), using something like [this script](https://gist.github.com/manuchandel/bc8a6ca4b1527b7594945e5091013905), or from [this archive of hot, toxic garbage](https://www.thetrumparchive.com/).
The JSON must be an array of objects, with each object containing either a `text` or `full_text` key, whose value is the full text of that tweet. No other keys are used.
e.g.
```JSON
[
{
"source": "Twitter for iPhone",
"text": "Who can figure out the true meaning of \"covfefe\" ??? Enjoy!",
"created_at": "Wed May 31 10:09:22 +0000 2017",
"retweet_count": 85555,
"favorite_count": 209543,
"is_retweet": false,
"id_str": "869858333477523458"
},
{
"source": "Twitter for iPhone",
"text": "Despite the constant negative press covfefe",
"created_at": "Wed May 31 04:06:25 +0000 2017",
"retweet_count": 127507,
"favorite_count": 162788,
"is_retweet": false,
"id_str": "869766994899468288"
}
]
```
### Running the Code
Clone this repo, symlink your tweet archive, then start a REPL using the provided init script:
```shell
$ git clone https://github.com/pmonks/fake-tweets.git
$ cd fake-tweets
$ ln -s /path/to/your/tweet-archive.json hot-toxic-garbage.json
$ clj -i init.clj -r
```
This will load and analyse the given tweet archive, then generate one fake tweet up to 100 "words" in length. To generate more:
```clojure
(ft/fake-tweet markov-chain)
```
In addition to the `markov-chain` var, the init script also initialises vars named `vocabulary`, `vocab-freq` and
`sorted-vocab-freq` which allow primitive analysis of the tweeter's vocabulary using standard Clojure functions:
```clojure
; How bigly is the tweeter's vocabulary? Note: punctuation, numbers, emojis, hashtags, @mentions etc. are all included in the count
(count vocabulary)
; Does the tweeter excrete covfefe?
(not (empty? (filter #(s/includes? (s/lower-case %) "covfefe") vocabulary))) ; Not idiomatic Clojure, but I don't agree with the rationale...
; How much?
(get vocab-freq "covfefe")
; What are the tweeter's favourite 100 words?
(take 100 sorted-vocab-freq)
```
## Contributor Information
[GitHub project](https://github.com/pmonks/fake-tweets)
[Bug Tracker](https://github.com/pmonks/fake-tweets/issues)
## License
Copyright © 2020 Peter Monks Some Rights Reserved
[](http://creativecommons.org/licenses/by-nc-sa/4.0/)
This work is licensed under a [Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License](http://creativecommons.org/licenses/by-nc-sa/4.0/).
SPDX-License-Identifier: [CC-BY-NC-SA-4.0](https://spdx.org/licenses/CC-BY-NC-SA-4.0.html)