Dankenstein

Dankenstein is a Markov Chain Twitter Bot generator, based on making a mashup of different corpora.

It is described in this blogpost.

Dependencies

The software itself is implemented using Bash, Make, and Python.

You'll need a Twitter Account and a Twitter application. From the latter, you'll need a consumer key, a consumer secret, an access token and an access token secret.

Enter these into twitterCredentials.sh

To generate the supported datasets you'll need :

Poppler
- brew install poppler on macOS
- sudo apt-get install -y poppler-utils on Ubuntu

After that, you can run the importEnv.sh script in the dev-folder. This will create a Python virtual environment (conda if you have it, virtualenv otherwise) called dankenstein, and install all python-dependencies.

If you'd rather install them separately, they are: Tweepy, darklyrics, wikiquote, markovify; (optionally nltk)

Usage

Usage is based around Make. The following options are available:

make corpora:

    Builds all corpora



make list:

    Lists all available corpora



make combinations:

    Prints all possible combinations of two candidates - may include duplicates (with switched positions)



make model ARGS="corpus1 corpus2 [(scale1 scale2) stateSize overlapTotal overlapRatio tries sentences modelComplexity]":

    Generates a model based on two corpora (the only required args).



    If you define scale 1, you must define scale 2.



    All options inside the square brackets are optional.



    ARGS:

        corpus1

            string - the name of the first corpus

                no default



        corpus2

            string - the name of the second corpus

                no default



        scale1

            float/int - scale of corpus1 relative to corpus2

                defaults to 1



        scale2

            float/int - scale of corpus2 relative to corpus1

                defaults to 1



        stateSize

            int - state size of the Markov chain

                defaults to 2



        overlapTotal

            int - maximum sequential words that overlap with a sentence from the corpora

                defaults to 15



        overlapRatio

            int - maximum percentage of overlap with a sentence from the corpora

                defaults to 70



        tries

            int - attempts to make an original sentence

                defaults to 10



        sentences

            int - number of sentences

                defaults to 5



        modelComplexity

            string - naive | expert

                defaults to "naive"



    EXAMPLE:

        make model ARGS="tcm jobs 2 1 2 15 30 10 25 expert" && make sentences



make sentence:

    Outputs one sentence based on an available (previously trained) model.



make sentences:

    Outputs the amount of sentences given as an argument during model generation.



make clean:

    Deletes all corpora.



make tweet:

    Posts a tweet.

It is possible to se all combinations for a given candidate, e.g. make combinations | grep "picard +".

Deployment:

Twitter secrets are set via environment variables, e.g.

export CONSUMER_KEY="consumer_key"

export CONSUMER_SECRET="consumer_secret"

export ACCESS_KEY="access_token"

export ACCESS_SECRET="access_token_secret"

An example deployment is described in the bottom of this blogpost.

dankensteinMarkov Chain Twitter Bot generator

Dankenstein

Dependencies

Usage

Deployment: