Project Overview:

The Social Media Buzzword Bot (SMBB) is a platform-agnostic twitter bot that detects social media keywords by polling twitter. It then is supposed to respond if the tweeter is deemed an influencer (as determined by their Klout score, which as we all know, is the ultimate value of one’s worth as a human being). The SMBB is interactive, with a focus on dynamic responses based on user-generated content. The content of the responses is constructed from a series of crowdsourced responses to ensure authenticity. SYNERGY SYNERGY SYNERGY, SYNERGY SYNERGY, SYNERGY SYNERGY.

More in Depth:

The Social Media Buzzword Bot (@BuzzwordBot on twitter) searches twitter for any of the following keywords:

influencers
go viral, going viral
crowdsourcing
user-generated content
earned media
authenticity, authentic branding
synergy
platform-agnostic
monetization
conversion rate
twitter ROI
facebook ROI
web 2.0
information superhighway
organic conversation
cloud computing
government 2.0
social capital
linkbuilding

Then, @BuzzwordBot decides whether or not tweet back. If it does, it has a 20% chance of tweeting a generic response: such as

Here, it inserts the keyword searched for into one of three generic phrases. Otherwise, it goes into a more specific response, where it chooses randomly between a couple responses customized to the keyword. I’ve selected a few below:

Process Overview

There are few things I hate in this world. Dictatorships. Censorship. Internet Marketing Buzzwords.

When my first concept for an AR system proved to gimmicky to implement, I looked around a bit for inspiration to do some sort of interactive social commentary project. Over break, a lot of my friends went to SXSW, which meant that my twitter feed was suddenly clogged with buzzword-filled retweets of various social media and internet marketing firms, people talking about Klout scores, etc, etc.

I decided to build a commentary on internet marketing buzzwords using as many social media buzzwords as possible. I started by picking a platform (twitter a natural choice), then decided I would automate some system to comment snarky things about the overuse of buzzwords on twitter. I also wanted to ensure I would be using as many buzzwords as possible in the implementation of my project. I began with some nice crowdsourcing.

Some of it was helpful:

Some of it was not:

Initial Thoughts:

I’m not sure whether the snark is enough to make this really work. Now that people have started to respond the the bot, things are pretty good. Definitely going to keep this running until I get reported for spamming the crowdsourcing.org twitter account (can I help it if EVERY tweet you send has a buzzword in it?). I also wish I had a larger response base, which given the quick nature of the hack, was an impossibility. I’ve decided against crowdsourcing the remaining responses, because I feel like the level of snark would drop too far. The code needs some more improvements to stop from tweeting on accidental use of phrases.

Update:

I got back today to the following:

It appears the reign of the twitterbot has ended: but not after making some waves (not to mention providing a few laughs).

Some People Enjoyed The Responses:

Some were small retweeters:

Some had a decent number of followers:

Some didn’t appreciate it the snark:

Some REALLY didn’t appreciate it:

Some liked the humor:

For some, it was the social commentary aspect:

Some sympathized with it:

Some even agreed with it:

A Few Final Stats:

Tweets Sent:

1314

Followers:

36

Replies:

24

Retweets:

16

Average Followers of each Account Retweeting:

927

Total Impressions:

approx. 16153

My satisfaction with the project has increased quite a bit since my first launch. After people starting interacting with the bot, applying their own meanings and insights into its actions, BuzzwordBot became more than me being snarky to random people and became an actual piece of interactive art. The fact that so many people saw Buzzword (and that some of them actually liked it) really made me happy.