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Well the Wired contest to come up with an epitaph for the Mars Phoenix lander has ended and the final choice blows, in my opinion.
Veni, vidi, fodi. (I came, I saw, I dug)
The number three choice wasn’t so bad:
It is enough for me. But for you, I plead: go farther, still.
My choice, as I mentioned before, was ranked at #4, so not too bad. I scrolled down to the very end of the list and looked for the most hated epitaphs. There were some real stinkers, to be sure, but also some funny ones. Here are several of the turdiest:
- this weather gives new meaning to the old saying, ‘blue balls in a nor’easter’
- May he rest in peace ~~~Lance was here ‘69~~~
- Go to the light. Like great men and myths, (Elvis, Tupac, BigFoot, Nessie) your legend will live on after your tweetstream goes flatline.
- Better Dead on Red. The First of what will be many efforts to raise us from the mire of our own making.
Twitrratr is a new service that attempts to do sentiment analysis on Twitter (follow me while you’re at it). According to their about page, they started off by tracking opinions on Obama but have since expanded to any term. Enter a keyword and it searches twitter for occurrences. It then assigns a sentiment to each post and returns percentages of positive, neutral, and negative tweets for that word. You can also track your own sentiment by searching for @your-username. I come up neutral, but there’s not a lot of data to go on there.
Their method appears to be fairly simple. They have a collection of adjectives with sentiment values (negative, positive) and based on what appears in a given tweet, they can classify a sentence. Of course, this is probably low recall (meaning it misses a lot of tweets that do express sentiment) since sentiment can be expressed without using adjectives. I’m not sure if it tries to do anything with negation, but so far my scans of results look like it ignores it.
So even though it’s pretty ghetto, it’s a nice toy. If they care to extend the algorithm, they have some pretty cool data to work with. I think it would be cool to get some (possibly donated, probably not paid) human effort together to tag some of their data to release as a research dataset.
Thanks to TwitPic, I can post these pics directly to twitter from my cell phone. Good times.
A couple of days ago, I wrote a script that would tweet anything you plurked. Thanks to some code from Neville Newey (based on PHP code by Charl van Niekerk), the plurk.py script I wrote has been updated to both plurk your tweets and tweet your plurks. This should work on both windows and linux machines. If you have access to a linux machine, I suggest setting up a cron job to take care of this. As I mentioned in the previous post, if you set up a cron job, be sure to change the path to plurkdb.dat to an absolute path. I have done the most testing on this with python 2.4 in linux.
This code is open source under the Creative Commons 3.0 Attribution license that this blog uses Creative Commons BSD license. Neville’s code appears to be under CC:Attribution 2.5 for South Africa, by what I could glean from his site. I have considered making this an open source project under Google code but have yet to take it all the way. Google sets a lifetime limit of 10 projects, so I will continue to hoard those against future need. If you make modifications to the code, please let me know and I will probably post them here and in the code for future releases, so we all win.
Note that the command line parameters have changed:
plurk.py <twitter username> <twitter password> <plurk username> <plurk password>
And of course, as with all software, use at your own risk.
If you want to use Plurk, but aren’t ready to leave Twitter, I wrote a little python script you can use to automatically mirror your plurks on Twitter. This will not work for response plurks, but your main plurks will be extracted and posted to your Twitter account with the prefix “plurking:” followed by your plurk.
The resulting tweet looks like this:
Download the script and set it up as a cron job (or you could execute it manually). It should work with python 2.4 and later. It stores a plurkdb.dat file (which you should probably assign an absolute path to, depending on the behavior of cron on your system). This file is checked every time it is run to make sure that duplicate plurks aren’t being tweeted. You should pass the following parameters on the command line (or modify the script so they are hardcoded, if you want): <twitter username> <twitter password> <plurk username> <plurk password>. Update: see later post on updated plurk script. And like with all software, use at your own risk.
Please let me know if you have any problems with it or see room for improvement. I hacked this out in a hurry, so …
Is it Hallowe’en already? A fellow nlp blogger (and twitterer) pointed me to Plurk just a few minutes ago. I have been messing with Twitter’s api over the past couple days, which hasn’t been as easy as you’d think since they are suffering from massive growing pains. Fetching the public timeline takes between 5-30 seconds. However, they just got like $15 million in funding, so maybe they’ll be able to address the issue. The even bigger question is can they turn this free advertising service (which is what it is partially becoming) into a revenue stream?
Plurk is basically Twitter with a makeover and some extra social features thrown in. It still has the 140 character status update style interface, but includes a function selection for each plurk (what they call qualifiers): you can say, think, ask, wish, etc. You can also add smileys. Rather than appearing as a series of boxes scrolling down the screen, your plurks appear as floating boxes on a side-scrolling timeline. Plurks of friends also appear on this timeline and the result is a more graphical and pleasing (to me) interface. You can reply directly to other plurks in the boxes and conversations are tracked very nicely. This is far superior to twitter, which requires you to visit the other person’s timeline and wade through their tweets to find previous tweets in a thread. With Twitter being slower than a drunken monkey with three broken legs, that’s even harder.
As my esteemed colleague pointed out, however, scaling is an issue for any service like this. Ultimately, you are bound by how fast you can access the database. If Plurk becomes as popular as Twitter (and I have every reason to believe it won’t), it will also become bogged down. Also, Plurk is just getting started and has no discernible API (unless I’m just missing it). Twitter already has quite a few third party apps.
I must say, though, I am sorely tempted to abandon Twitter in favor of Plurk just for the fact that Plurk is accessible. The massive lag of Twitter is getting to me. Of course, if no one is there to listen to my ramblings, what’s the point?
There is nothing unusual about verbing nouns in English. Despite the fact that your English teacher may have told you not to do this, it is common practice, especially on the intarwebs. Verbing brand names to mean the primary action performed by the chief product of that brand is less common, but we all know about “googling.” Just sitting here, trying to drink my morning coffee, I couldn’t come up with another example.
But what got me thinking about this is another example used in today’s User Friendly. One character says,
“You’re gonna ebay it to goths, aren’t you.” [emphasis mine]
I had never heard the brand name ebay used in verb form, meaning to sell something on ebay (the primary function of their chief product). It is not uncommon, though. Searching the Google for +”to ebay it”, I found that at least 10% of the top few pages of results were just this construction (versus “to ebay. It …”). I estimate from that there are about 19,000 uses of ebay as a verb in this context, and no doubt many others in variations (e.g. “I ebayed my watch”).
Another example that just occurred to me, but which is pretty artificial, is to twitter, meaning to post something on Twitter. I say this is artificial because Twitter openly encourages and suggests this terminology. It was not an emergent construct, but an imposed one. It has been adopted by the overwhelming majority of users, though. [follow me on twitter]
So here is my question: does this only work for Internet companies? I’m probably forgetting some obvious brick-and-mortar company for which we have verbed their brand, so please tell me if I have. Or is it that Internet companies are especially conducive to this construction because so many Internet companies start off with only one service and become known by that service. Google is search, ebay is selling crap through auctions, twitter is … twittering. If this only works for Internet companies, why did we start doing it in the first place?
And I just came up with a brick-and-mortar example: hoover. You can hoover down a plate of food, meaning to suck something up like a champ. But my classification still holds, that is the primary function of their chief product (or at least the main product that people know them by). Marketing people have already taken this to heart, I’m sure. You need an easy name that sounds like English. Just like with scientific terminology, no one wants to Dinklefwat their dishes.
