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The saintbletch "Hilarious fun with words" thread


saintbletch
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Buctimbu?

 

OK, just this once and mainly to ****-off Toke by seeming to favour you over him, I'm going to allow that suggestion even though you didn't quote the post in question.

 

You're wrong anyway, but, and look at me being a tart here, post 299 isn't BTT...

 

(The power of the ellipsis, eh?)

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Hey, bletch, these word clouds are great, I’m only too sorry they’ve passed me by these last few days.

 

Glad you're enjoying the hilarious fun that can be had with words, Halo. Toke is too, but he's a little reticent about admitting it.

 

Could you use them to do some in depth psychological profiling – rank posters in order of Saintliness or insaneness etc?

 

 

 

Well, now you ask Halo, you can do all sorts of analysis on the text. You can form impressions and trends from the text, rather than being able to draw cast iron conclusions. So alas, nothing I do will end up getting some of the main-boarders detained for 28 days under the influence of messrs valium and zanax.

 

What I can do is gain an idea of the sentiment and subjectivity of a post, poster, thread, forum, etc. This means I can then compare each of these results with other results.

 

So questions such as "Is Alpine_saint more negative than the notional average poster", can be 'answered'. I can also then combine things and compute the 'average' sentiment in specific noun-phrases - such as whether the forum is on 'average' positive when I detect the presence of specific tokens - such as "cortese", "lambert", "lallana" and so on. I can then look at that temporally - so I can see if the attitude towards "Hooiveld" has changed over time, and at what time it started to change. I can also look at things like verb usage and correlate that with Saints' results, to see what sort of language gets used after wins, losses, draws, etc. I can ask questions such as which posters have contributed the most negatively to threads that got locked.

 

But all of this comes with a mass of caveats. For example, not every poster uses the Queen's which leads to less accuracy, and so many memes, some specific to TSW, need to be classified (woot, nuns, facepalm, clappy, clappie, clappies, happies, bedwetters, etc.). Also, this might come as a surprise, but some posters dominate discussions. Having a significant portion of a thread contributed by one poster can really skew results. Another issue is the use of sarcasm. I am also blind to the real meaning of posts by Turkish and CB Fry because they unremittingly rely on sarcasm (woosh!), which would skew my 'understanding' of their 'work'.

 

It's possible to get around all of these problems, but it involves a lot of effort in training a program. This means looking, sentence by sentence, at posts and manually classifying them. Once done, this manual classification can then be taken and used in an automated way.

 

This is all a branch of computer science called Natural Language Processing. It, and a subset called Sentiment Analysis, are used to mine the words we excrete into electronic social interactions every day. Organisations and companies want to know what we think about their products, services, competitors, government policies, opposition, secret services, etc. Work in this area is really taking off, and I'm benefitting by standing on the shoulders of some really smart people that have made this accessible to hobbyist such as me. I'm not a proper programmer any more, I used to develop for a living many years ago, so this is all a bit of a sideline now.

 

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Wouldn't that mean that you were writing those things about other people - in reply to me, perhaps?

 

No most of my posts are about me me me. I find people - understandably - prefer it that way. I do associate some adjectives and indeed one particular verb with you though Bletch, so you're in my thoughts.

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Glad you're enjoying the hilarious fun that can be had with words, Halo. Toke is too, but he's a little reticent about admitting it.

 

 

 

 

 

Well, now you ask Halo, you can do all sorts of analysis on the text. You can form impressions and trends from the text, rather than being able to draw cast iron conclusions. So alas, nothing I do will end up getting some of the main-boarders detained for 28 days under the influence of messrs valium and zanax.

 

What I can do is gain an idea of the sentiment and subjectivity of a post, poster, thread, forum, etc. This means I can then compare each of these results with other results.

 

So questions such as "Is Alpine_saint more negative than the notional average poster", can be 'answered'. I can also then combine things and compute the 'average' sentiment in specific noun-phrases - such as whether the forum is on 'average' positive when I detect the presence of specific tokens - such as "cortese", "lambert", "lallana" and so on. I can then look at that temporally - so I can see if the attitude towards "Hooiveld" has changed over time, and at what time it started to change. I can also look at things like verb usage and correlate that with Saints' results, to see what sort of language gets used after wins, losses, draws, etc. I can ask questions such as which posters have contributed the most negatively to threads that got locked.

 

But all of this comes with a mass of caveats. For example, not every poster uses the Queen's which leads to less accuracy, and so many memes, some specific to TSW, need to be classified (woot, nuns, facepalm, clappy, clappie, clappies, happies, bedwetters, etc.). Also, this might come as a surprise, but some posters dominate discussions. Having a significant portion of a thread contributed by one poster can really skew results. Another issue is the use of sarcasm. I am also blind to the real meaning of posts by Turkish and CB Fry because they unremittingly rely on sarcasm (woosh!), which would skew my 'understanding' of their 'work'.

 

It's possible to get around all of these problems, but it involves a lot of effort in training a program. This means looking, sentence by sentence, at posts and manually classifying them. Once done, this manual classification can then be taken and used in an automated way.

 

This is all a branch of computer science called Natural Language Processing. It, and a subset called Sentiment Analysis, are used to mine the words we excrete into electronic social interactions every day. Organisations and companies want to know what we think about their products, services, competitors, government policies, opposition, secret services, etc. Work in this area is really taking off, and I'm benefitting by standing on the shoulders of some really smart people that have made this accessible to hobbyist such as me. I'm not a proper programmer any more, I used to develop for a living many years ago, so this is all a bit of a sideline now.

 

 

:adore:

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You are missing a very interesting discussion on the butterfly effect on the main board bletch. The conclusion seemed to be, no matter how many butterflies you had in effect the best you could hope for is for some old man to stop messing with your junk. You were never going to bone Amy whatshername or play Hull in the quarter final. MLG confirmed this as it is tough at Uni and they are never wrong.

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You are missing a very interesting discussion on the butterfly effect on the main board bletch. The conclusion seemed to be, no matter how many butterflies you had in effect the best you could hope for is for some old man to stop messing with your junk. You were never going to bone Amy whatshername or play Hull in the quarter final. MLG confirmed this as it is tough at Uni and they are never wrong.

 

On a butterfly related topic, my Mrs gave me a butterfly kiss last night, at least that's what she said it was called. Personally I'd just say she was blinking too close to my face and her eye lashes were touching my face. I have no idea why someone decided to call that a butterfly kiss, that's girls for you I guess, odd.

 

But here's some instructions with pictures Tokyo would like, in case you want to give it a go.

http://www.wikihow.com/Butterfly-Kiss

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Toke, was that your Thomas Hitzlsperger moment?

 

2014_02_17_12_11_28.jpg

 

Is this you trying to tell us all something?

 

Because you should know that nobody in TMS will judge you for admitting to those contradictory, squirly, perineum-centered feelings that you get when you and your dogs 'accidentally' disturb a couple of rutting 'bears' on the common on Sundays.

 

FYI you shouldn't eat meat on the sabbath - or roll on the shabbos. Probably.

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You are missing a very interesting discussion on the butterfly effect on the main board bletch. The conclusion seemed to be, no matter how many butterflies you had in effect the best you could hope for is for some old man to stop messing with your junk. You were never going to bone Amy whatshername or play Hull in the quarter final. MLG confirmed this as it is tough at Uni and they are never wrong.

 

I have just seen that.

 

The question remains...If a tree falls on MLG in the woods and nobody is around to see it, does anyone give a ****?

 

He is right, though.

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I think I made a mistake with the spelling spud. Urban dictionary has it as "a Rusty Trombone

To get rimmed whilst recieving a hearty reach round, thus resembling a trombone player in full chorus."

 

It is then followed by "While receiving a rusty trombone I lost control of my bowels." This is a little disconcerting for those in the orchestra. Butterfly kissing is a 'Gateway' act I believe. This time next month, you may be playing a different tune.

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Tom Waits, apparently. Who for? No man.

 

Kim Il Sung to his children, but it didn't help them turn out nice.

 

Another Kim Clijsters, but only when she's really annoyed.

 

Jeremy Irons, but he leaves the washing-up to his wife.

Edited by Fowllyd
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Glad you're enjoying the hilarious fun that can be had with words, Halo. Toke is too, but he's a little reticent about admitting it.

 

 

 

 

 

Well, now you ask Halo, you can do all sorts of analysis on the text. You can form impressions and trends from the text, rather than being able to draw cast iron conclusions. So alas, nothing I do will end up getting some of the main-boarders detained for 28 days under the influence of messrs valium and zanax.

 

What I can do is gain an idea of the sentiment and subjectivity of a post, poster, thread, forum, etc. This means I can then compare each of these results with other results.

 

So questions such as "Is Alpine_saint more negative than the notional average poster", can be 'answered'. I can also then combine things and compute the 'average' sentiment in specific noun-phrases - such as whether the forum is on 'average' positive when I detect the presence of specific tokens - such as "cortese", "lambert", "lallana" and so on. I can then look at that temporally - so I can see if the attitude towards "Hooiveld" has changed over time, and at what time it started to change. I can also look at things like verb usage and correlate that with Saints' results, to see what sort of language gets used after wins, losses, draws, etc. I can ask questions such as which posters have contributed the most negatively to threads that got locked.

 

But all of this comes with a mass of caveats. For example, not every poster uses the Queen's which leads to less accuracy, and so many memes, some specific to TSW, need to be classified (woot, nuns, facepalm, clappy, clappie, clappies, happies, bedwetters, etc.). Also, this might come as a surprise, but some posters dominate discussions. Having a significant portion of a thread contributed by one poster can really skew results. Another issue is the use of sarcasm. I am also blind to the real meaning of posts by Turkish and CB Fry because they unremittingly rely on sarcasm (woosh!), which would skew my 'understanding' of their 'work'.

 

It's possible to get around all of these problems, but it involves a lot of effort in training a program. This means looking, sentence by sentence, at posts and manually classifying them. Once done, this manual classification can then be taken and used in an automated way.

 

This is all a branch of computer science called Natural Language Processing. It, and a subset called Sentiment Analysis, are used to mine the words we excrete into electronic social interactions every day. Organisations and companies want to know what we think about their products, services, competitors, government policies, opposition, secret services, etc. Work in this area is really taking off, and I'm benefitting by standing on the shoulders of some really smart people that have made this accessible to hobbyist such as me. I'm not a proper programmer any more, I used to develop for a living many years ago, so this is all a bit of a sideline now.

 

 

All that non-muppet stuff is actually really fascinating, speaking as one of quite a few wordists on this forum (you may say pedant). Interesting that it is called NLP, as I do believe you use the other NLP when leading your flock of performing seals in the Muppet Show! :-) I meant frequency ordered lists of words or proponderance analysis but I didn't want to lower the tone, and I was just trying to be funny, which I am actually incapable of. That's why I like the muppet show, to remind myself of what humour is.

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What does any of this mean?

 

shhh, don't tell anyone but we're being programmed neurolingustically (my spell checker has a problem with that word but won't offer a viable alternative, so I'm going with the hope I've spelt it correctly)

 

Suggested prep for this thread is the Manchurian Candidate! If you find yourself standing in the middle of the street with blood on your clothes and no clue how you or it got there then Bletch's work is complete.

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If you find yourself standing in the middle of the street with blood on your clothes and no clue how you or it got there then you'll know your 2nd date went badly.

 

Fixed it for you S&M

 

Sounds like an adrenalin packed night out to me.

Edited by buctootim
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