Yes, I built a Twitter bot. My bot tweets random, nonsensical wine reviews (you can find it here @WineSnobBot).
of fresh peaches, this low-alcohol effort is further bolstered by sémillon, this is now past its peak.
I know what you are all asking – WHY?I have been working recently on a variety of projects. One of them included getting a new server running at the house to mine data and run various other automated scripts. As usual, these projects get bigger and bigger and I haven’t been able get much out the door.Then I heard on one of my new favorite podcasts, Partially Derivative, about the Beer Snob Says twitter bot, by Greg Reda. It was such a fun sounding project and he posted the code on GitHub. Greg does an incredible job explaining the process behind the Markov Chains in the code that generates the reviews and I thought it would be fun to experiment with.I decided a wine review bot would be a good challenge, so I plotted out a plan in three parts: getting data, modifying the Markov generator and automating a bot to post the results to Twitter.Like any Markov process, the inputs are key. I needed a massive amount of data (real reviews) to make this work. Greg mentions this in his article, stating your likelihood of a more readable random tweet increases as you increase the size of the corpus.I started with a few sites and quickly ran into problems. I just couldn’t get enough reviews that were well-written enough to be consistent. Many were amateur reviews with sloppy language.I eventually found one site that had a database of about 100,000 short reviews of 40-60 words dating from 2000 to the present. I will delve into where more at a later date, since I somehow got away with over 12,000 calls to their website one night. I also plan on combining a few more sources in the future.So now I have a corpus of over 4 million words. One of the things I first noticed was that certain punctuation works better than others – commas and periods look better in random sentences than parenthesis, colons and semi colons. The result thus far looks like this:
the palate, though it’s infused with creme de cassis, dark chocolate, grilled bacon, fine herbs comprise the nose.
You will notice it is all lowercase. It just seems to make more sense when it’s all lowercase, rather than just random capitalization. I plan on capitalizing the first word and any subsequent words after periods, but haven’t as yet.
angeles—a cool-climate, coastal pinot, especially one that’s amply balanced by orangy acids. —this is a wine to foreign markets.
I am also torn about dashes. They seem to crop up in numbers. The division of words like Los Angeles also concerns me, but I’m still formulating my thoughts on proper nouns.To this point, I needed to get the Markov process running a little better. I started with the basic Python script Reda created and added a few new rules. One rule is to not start a tweet with the word ‘and’. The word ‘with’ is a tougher call, but for now I am keeping it simple.
smooth, honeyed finish. grenache, cinsault and grenache are prevalent in the initial taste is your style.
Here you can see some work still needs to be done on the Markov process. A layer to possibly eliminate duplication of ‘complex’ words, like Grenache, might help. One thought is to test words in length greater than 5 and force a redo when any are duplicated.Lastly I needed to automate it. Since my python program will reside on a Mini Mac server, I created a Launchd file to fire off the bot every 4444 seconds (about one hour and 14 minutes). Within the python code, I create a tweet, using Twython, and save it to a file (so I can check the language and perfect the code) but only actually tweet approximately every one in six times (randomly generated of course). I figure a bot tweeting about four times a day is enough.This is obviously a work in progress. The first order of business was to get it out the door. The next part is to improve the logic it uses to craft the tweets. Please follow along and let the Wine Snob Bot know what you think. I will post code and more details in the future.