Here’s a freecycle ad that I found to be quite poetic. All newlines were inserted later and were not part of the original post. The link at the end leads to the original posts but will only work if you are a member.
<quote>
Offered.
pink drinking glass.
Broken.
A bit weird
maybe
It’s a drinking glass
pink coloured
about a half pint.
It has broken
and a slice
has cracked off of it.
Maybe,
just maybe,
someone is local enough
and can
make use of it
for arty purposes?
Otherwise
it’ll end up
wrapped in newspaper
in the tip.
No?
Collect
CB4.
</quote>
http://groups.yahoo.com/group/cambridgefreecycle/message/206022
A paper on “Positivity of the English Language” caught the attention of the main stream media recently. It claimed that English words exhibit a “clear positive bias”. The authors (which happen to be Mathematicians) based this conclusion on their analysis of data from tweets, books, news articles and song lyrics in English. The results showed that people used more positive words than negative ones. In spite of the fact that frequency based analysis is not exactly new in Computational Linguistics and the spread of this article in the media might be a good example for understanding why some news items receive more attention than others, the experiment is interesting nevertheless and finding out if other languages behave the same might be more intriguing.
While search engines can be used to perform this tasks, words are not the only source of conveying emotions in the digital world. Since the invention of the smiley, emoticons have played a major role in attaching sentiment to online text. There have been studies about utilizing emoticons for detecting sentiment in different text genres but most search engines do not support the query structure which returns results when searching for emoticons. The obvious solution is to have your own snapshot of the web and do a text search but this approach has always required a lot of storage and processing resources. Until now.
Blekko has introduced a WebGrep service which searches for your text in 4 billion pages but using text patterns instead of words. I will not hesitate to use the words ‘pretty cool’ to describe it. As a simple test, I’ve tried comparing a smiley face with a sad face emotion to gauge the total mood of the web. Sadly [sic], for 142 million sad faces (assuming one sad smiley per page), there are only 104 million happy ones (click here for details). While these statistics can be improved by including variants of existing emoticons, it might be taken as an indication that we need to be more happy.
One way to make that happen is to consciously avoid using sad emoticons when chatting and blogging (as in this post). We can then claim that we are making the web a better place, one smile at a time 
!
Today, I got a copy of the policy guidelines against sexual harassment in institutions of higher learning in my inbox which has been published by the Govt. of Pakistan Higher Education Commission. It contains a “listing of sexual harassment” along with “actual reported cases”. The last item in the list is
Forcing students to publish their research work in Supervisors name.
While the most obvious implication of this statement is that plagiarism (by the supervisor) is sexual harassment, I think there is a hidden message there as well.
Research is sexy! 
Another example of sexual harassment as stated in the document is
Younger faculty member was blocked by Dean of the relevant faculty to get higher education (PhD/Phil).
Here, I’ll leave you to make your own implications. Write them in the comments, if you will, and read the whole document for more lols.
Ash Court at Girton. I should get more pictures of my college… someday.
outside university library
If you walk into my department, one of the first things you may notice is that some of the tiles on the floor are a black and there’s no particular pattern to it. These tiles actually encode a message. The curious amongst us are supposed to decode this but despite having spent 3 years in the department, I could never get the time until last Friday. The decoding should be pretty simple if you want to try your skills. The last 6 letters of the first word can be read off this picture. If you are too lazy, just click here for the explanation. (Anyone who has taken an Introduction to Computer Science course should at least try for ONE minute before clicking)
The code says : Computer LAboratory — AD 2001 — ☻. If you look closely, the tiles are in the form of squares and some of them are split in the middle such that the left half is always black and the right one is always white. Take each black-white combo as a 1 and the white-white combo as a 0. It’s a straight forward UTF encoding after that. Foe example, the row closest to the bottom of the pic is WWBWBWWWWWWWWWBW, where W is white an B is black. Taking WW = 0 and BW = 1, the code becomes 01100001 i.e. 97 in decimal and its ASCII equivalent is ‘a’.
Geek Art!
(Oh! and clicking on the image opens up a high res version.)
