Re: [backstage] Mood News 3
Kim Plowright wrote: Wow - that's a slightly terrifying concept: the ability to filter news according to your personal preferences so you only get 'good' news delivered to you... Very 1984. *Shudder* Not quite - if you only received good news because thats all you were able to get/all you were given, that would be 1984. Otherwise, its just self inflicted News Delusion and happiness. The sort of thing experienced whilst watching anything with Lorraine Kelly in it. -- Use of advanced messaging technology does not imply an endorsement of western industrial civilization - Sent via the backstage.bbc.co.uk discussion group. To unsubscribe, please visit http://backstage.bbc.co.uk/archives/2005/01/mailing_list.html.
Re: [backstage] Mood News 3
How happy I was to hear the name of Lorraine Kelly - a breath of fresh air to an expat in the US, and a Scot at that. Matt On 7/18/05, Brit [EMAIL PROTECTED] wrote: Kim Plowright wrote: Wow - that's a slightly terrifying concept: the ability to filter news according to your personal preferences so you only get 'good' news delivered to you... Very 1984. *Shudder* Not quite - if you only received good news because thats all you were able to get/all you were given, that would be 1984. Otherwise, its just self inflicted News Delusion and happiness. The sort of thing experienced whilst watching anything with Lorraine Kelly in it. -- Use of advanced messaging technology does not imply an endorsement of western industrial civilization - Sent via the backstage.bbc.co.uk discussion group. To unsubscribe, please visit http://backstage.bbc.co.uk/archives/2005/01/mailing_list.html. - Sent via the backstage.bbc.co.uk discussion group. To unsubscribe, please visit http://backstage.bbc.co.uk/archives/2005/01/mailing_list.html.
Re: [backstage] Mood News 3
Davy Mitchell wrote: As MN is getting a fair number of hits for its early stage in development, I have posted an update as it has moved on greatly. It's using much the same rating system. I've spent the time on reorganising the code, some DBase work, presentation and the client side stuff. It's an excellent concept, and very clever, however there are a few odd things there. For example, City agree Wright-Phillips fee. Now this is good news for Mr Wright-Phillips, and for Chelsea, but not good news for Manchester City. Therefore it should either be neutral, or does the system work on utilitarianism? Not a criticism, just more something that there may be a way of working round in the future. Although there probably isn't... -- From the North, this is Kirk www.broadcastingsights.org.uk - Sent via the backstage.bbc.co.uk discussion group. To unsubscribe, please visit http://backstage.bbc.co.uk/archives/2005/01/mailing_list.html.
RE: [backstage] Mood News 3
Isn't that the fundamental concern here. It is all relative to perspective... Good (or bad or Evil or whatever) are dependent on your point of view. Just think of election results. A really clever site would ask you for your point of view (or remember when you disagree) and adjust accordingly. A complex task though... -Original Message- From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] On Behalf Of Kirk Northrop Sent: Monday, July 18, 2005 5:06 PM To: backstage@lists.bbc.co.uk Subject: Re: [backstage] Mood News 3 Davy Mitchell wrote: As MN is getting a fair number of hits for its early stage in development, I have posted an update as it has moved on greatly. It's using much the same rating system. I've spent the time on reorganising the code, some DBase work, presentation and the client side stuff. It's an excellent concept, and very clever, however there are a few odd things there. For example, City agree Wright-Phillips fee. Now this is good news for Mr Wright-Phillips, and for Chelsea, but not good news for Manchester City. Therefore it should either be neutral, or does the system work on utilitarianism? Not a criticism, just more something that there may be a way of working round in the future. Although there probably isn't... -- From the North, this is Kirk www.broadcastingsights.org.uk - Sent via the backstage.bbc.co.uk discussion group. To unsubscribe, please visit http://backstage.bbc.co.uk/archives/2005/01/mailing_list.html. - Sent via the backstage.bbc.co.uk discussion group. To unsubscribe, please visit http://backstage.bbc.co.uk/archives/2005/01/mailing_list.html.
RE: [backstage] Mood News 3
A really clever site would ask you for your point of view (or remember when you disagree) and adjust accordingly. A complex task though... A feedback neural network should be able to solve it reasonably straight-forwardly (although you would need a large sample of data with which to train the network on a per-user basis, which could also give large overheads) - its effectively spam-assassin for news, but slightly different. - Sent via the backstage.bbc.co.uk discussion group. To unsubscribe, please visit http://backstage.bbc.co.uk/archives/2005/01/mailing_list.html.
RE: [backstage] Mood News 3
its effectively spam-assassin for news, but slightly different. Wow - that's a slightly terrifying concept: the ability to filter news according to your personal preferences so you only get 'good' news delivered to you... Very 1984. *Shudder* The mood would indeed only work effectively if it leant your preferences and filtered accordingly - in effect, the current system suggests that it is 'Bad news in the eyes of right thinking people' - it would look different if the intended audience was, say, Bond Villains. Thought - wonder if a system with user-based feedback loop would be effective at catching stories that are 'spun'? Ie, cross referencing a 'mood' against the yes/no votes of the users would yield some way of spotting editorial bias, or stories that are released to sweeten potentially damaging/worrying stories with palliative good news (not necessarily by the journalists, but maybe at source)? Have you thought about running a similar 'mood detector' through video transcripts, or ficiton? It could be a useful addition to a reccomendation engine? kim -Original Message- From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] On Behalf Of Luke Dicken Sent: 18 July 2005 11:13 To: backstage@lists.bbc.co.uk Subject: RE: [backstage] Mood News 3 A really clever site would ask you for your point of view (or remember when you disagree) and adjust accordingly. A complex task though... A feedback neural network should be able to solve it reasonably straight-forwardly (although you would need a large sample of data with which to train the network on a per-user basis, which could also give large overheads) - its effectively spam-assassin for news, but slightly different. - Sent via the backstage.bbc.co.uk discussion group. To unsubscribe, please visit http://backstage.bbc.co.uk/archives/2005/01/mailing_list.html. - Sent via the backstage.bbc.co.uk discussion group. To unsubscribe, please visit http://backstage.bbc.co.uk/archives/2005/01/mailing_list.html.
Re: [backstage] Mood News 3
That is why I called it an assumption. Actually, there is a distinction between subjective/objective language and subjective/objective statements. I could probably make a statement in objective terms that presents my subjective POV. Even the fact that I mentioned something can actually reflect a subjective POV :-) Matt On 7/18/05, Tim Scollick [EMAIL PROTECTED] wrote: news articles are objective. HAHAHAHAHAHA Just publishing an article is a subjective statement. Once you add the fact that virtually all large media conglomerates are owned by companies with corporate agendas outside of media and you will NEVER have objective mainstream news. Even a public broadcaster, like the BBC, has to have the larger interests and worldview of its democratic owner (the people of the United Kingdom) at heart. On 7/18/05, Matthew Hurst [EMAIL PROTECTED] wrote: There are a number of companies that are currently competing in the marketing intelligence space that have developed sentiment or polarity mining systems (Intelliseek, my employer, being one of them). The general buckets into which this work falls include 1) affect analysis - grokking the emotional content of text 2) polarity analysis - detecting author statements about favourable and unfavourable conditions or opinions 3) subjectivity analysis - are the statements subjective or objective? Ideally, journalism should be objective and so notions of affect (emotion) ought not to come into it unless reporting (objectively!) some other agent's feelings. However, there are plenty of issues that are favourable/unfavourable. The approach of a hurrican is unfavourable, the rescuing of a baby from a crocodile pit is favourable. This suggests thre requirements: 1) detection of favourable/unfavourable topics (bombs, murder, etc.) 2) tracking of the development of stories (person rescued from kidnappers) 3) the anlaysis of stories (rescue fro mburning building). #1 is probably reasonably well done with a keyword list and some knowledge of an article being the first in a story arc (potentially to be continued as the story develops). #2 is pretty hard, as is #3 I'd be interested in throwing our polarity system against the BBC news feed to see what happens when we ignore the assumption that news articles are objective. If I have the time to do this I'll report the results here... Matt Hurst http://datamining.typepad.com On 7/18/05, Kim Plowright [EMAIL PROTECTED] wrote: its effectively spam-assassin for news, but slightly different. Wow - that's a slightly terrifying concept: the ability to filter news according to your personal preferences so you only get 'good' news delivered to you... Very 1984. *Shudder* The mood would indeed only work effectively if it leant your preferences and filtered accordingly - in effect, the current system suggests that it is 'Bad news in the eyes of right thinking people' - it would look different if the intended audience was, say, Bond Villains. Thought - wonder if a system with user-based feedback loop would be effective at catching stories that are 'spun'? Ie, cross referencing a 'mood' against the yes/no votes of the users would yield some way of spotting editorial bias, or stories that are released to sweeten potentially damaging/worrying stories with palliative good news (not necessarily by the journalists, but maybe at source)? Have you thought about running a similar 'mood detector' through video transcripts, or ficiton? It could be a useful addition to a reccomendation engine? kim -Original Message- From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] On Behalf Of Luke Dicken Sent: 18 July 2005 11:13 To: backstage@lists.bbc.co.uk Subject: RE: [backstage] Mood News 3 A really clever site would ask you for your point of view (or remember when you disagree) and adjust accordingly. A complex task though... A feedback neural network should be able to solve it reasonably straight-forwardly (although you would need a large sample of data with which to train the network on a per-user basis, which could also give large overheads) - its effectively spam-assassin for news, but slightly different. - Sent via the backstage.bbc.co.uk discussion group. To unsubscribe, please visit http://backstage.bbc.co.uk/archives/2005/01/mailing_list.html. - Sent via the backstage.bbc.co.uk discussion group. To unsubscribe, please visit http://backstage.bbc.co.uk/archives/2005/01/mailing_list.html. - Sent via the backstage.bbc.co.uk discussion group. To unsubscribe, please visit http://backstage.bbc.co.uk/archives/2005/01/mailing_list.html. - Sent via the backstage.bbc.co.uk discussion group. To unsubscribe, please visit http://backstage.bbc.co.uk/archives
Re: [backstage] Mood News 3
Wow - thanks for all the emails. Uh, that's great, but I found this article: http://news.bbc.co.uk/1/ hi/health/4681707.stm in Bad news, when it should be good. Yeah - the scoring system needs to cover more topics and better. It is very crude however the next version should be much better and faster to extend. I wonder if now would be a good time to give some broad definition of what constitutes good and bad news. What a philosophical question! Mood News just tries to pick up and amplify the tone already in the story. There is no 'correct' categorisation even if a human did it. good news for Mr Wright-Phillips, and for Chelsea, but not good news for Manchester City. This is the tricky business of introducing domain knowledge. I'd only want to do that for a very specialised site e.g. a supporter site (political, sport) and even then it would be very hard. Wow - that's a slightly terrifying concept: the ability to filter news according to your personal preferences so you only get 'good' news delivered to you... Very 1984. *Shudder* I have a neat idea planned for filtering but I've stayed away *just* because of the spooky factor. Parental control might be a valid application of this. Filtering does seem to go against some of the idea of Mood News which is to broaden the range of stories read. Have you thought about running a similar 'mood detector' through video transcripts, or ficiton? It could be a useful addition to a reccomendation engine? Interesting idea - an objective measure of how up/down beat a novel or film is. Studios would love that esp. when going for a feelgood factor. Did you hear about the app that performs analysis of songs to see if they are going to be chart hits? I am sure it was on Slashdot.. it is all relative to perspective... Good (or bad or Evil or whatever) Indeed, Mood News offers one perspective of the news that is hopefully useful and interesting. Now back to my neutral Python... :-) Thanks again, Davy Mitchell - Sent via the backstage.bbc.co.uk discussion group. To unsubscribe, please visit http://backstage.bbc.co.uk/archives/2005/01/mailing_list.html.
Re: [backstage] Mood News 3
There are a number of companies that are currently competing in the marketing intelligence space that have developed sentiment or polarity mining systems (Intelliseek, my employer, being one of them). The general buckets into which this work falls include 1) affect analysis - grokking the emotional content of text 2) polarity analysis - detecting author statements about favourable and unfavourable conditions or opinions 3) subjectivity analysis - are the statements subjective or objective? Ideally, journalism should be objective and so notions of affect (emotion) ought not to come into it unless reporting (objectively!) some other agent's feelings. However, there are plenty of issues that are favourable/unfavourable. The approach of a hurrican is unfavourable, the rescuing of a baby from a crocodile pit is favourable. This suggests thre requirements: 1) detection of favourable/unfavourable topics (bombs, murder, etc.) 2) tracking of the development of stories (person rescued from kidnappers) 3) the anlaysis of stories (rescue fro mburning building). #1 is probably reasonably well done with a keyword list and some knowledge of an article being the first in a story arc (potentially to be continued as the story develops). #2 is pretty hard, as is #3 I'd be interested in throwing our polarity system against the BBC news feed to see what happens when we ignore the assumption that news articles are objective. If I have the time to do this I'll report the results here... Matt Hurst http://datamining.typepad.com On 7/18/05, Kim Plowright [EMAIL PROTECTED] wrote: its effectively spam-assassin for news, but slightly different. Wow - that's a slightly terrifying concept: the ability to filter news according to your personal preferences so you only get 'good' news delivered to you... Very 1984. *Shudder* The mood would indeed only work effectively if it leant your preferences and filtered accordingly - in effect, the current system suggests that it is 'Bad news in the eyes of right thinking people' - it would look different if the intended audience was, say, Bond Villains. Thought - wonder if a system with user-based feedback loop would be effective at catching stories that are 'spun'? Ie, cross referencing a 'mood' against the yes/no votes of the users would yield some way of spotting editorial bias, or stories that are released to sweeten potentially damaging/worrying stories with palliative good news (not necessarily by the journalists, but maybe at source)? Have you thought about running a similar 'mood detector' through video transcripts, or ficiton? It could be a useful addition to a reccomendation engine? kim -Original Message- From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] On Behalf Of Luke Dicken Sent: 18 July 2005 11:13 To: backstage@lists.bbc.co.uk Subject: RE: [backstage] Mood News 3 A really clever site would ask you for your point of view (or remember when you disagree) and adjust accordingly. A complex task though... A feedback neural network should be able to solve it reasonably straight-forwardly (although you would need a large sample of data with which to train the network on a per-user basis, which could also give large overheads) - its effectively spam-assassin for news, but slightly different. - Sent via the backstage.bbc.co.uk discussion group. To unsubscribe, please visit http://backstage.bbc.co.uk/archives/2005/01/mailing_list.html. - Sent via the backstage.bbc.co.uk discussion group. To unsubscribe, please visit http://backstage.bbc.co.uk/archives/2005/01/mailing_list.html. - Sent via the backstage.bbc.co.uk discussion group. To unsubscribe, please visit http://backstage.bbc.co.uk/archives/2005/01/mailing_list.html.
Re: [backstage] Mood News 3
news articles are objective. HAHAHAHAHAHA Just publishing an article is a subjective statement. Once you add the fact that virtually all large media conglomerates are owned by companies with corporate agendas outside of media and you will NEVER have objective mainstream news. Even a public broadcaster, like the BBC, has to have the larger interests and worldview of its democratic owner (the people of the United Kingdom) at heart. On 7/18/05, Matthew Hurst [EMAIL PROTECTED] wrote: There are a number of companies that are currently competing in the marketing intelligence space that have developed sentiment or polarity mining systems (Intelliseek, my employer, being one of them). The general buckets into which this work falls include 1) affect analysis - grokking the emotional content of text 2) polarity analysis - detecting author statements about favourable and unfavourable conditions or opinions 3) subjectivity analysis - are the statements subjective or objective? Ideally, journalism should be objective and so notions of affect (emotion) ought not to come into it unless reporting (objectively!) some other agent's feelings. However, there are plenty of issues that are favourable/unfavourable. The approach of a hurrican is unfavourable, the rescuing of a baby from a crocodile pit is favourable. This suggests thre requirements: 1) detection of favourable/unfavourable topics (bombs, murder, etc.) 2) tracking of the development of stories (person rescued from kidnappers) 3) the anlaysis of stories (rescue fro mburning building). #1 is probably reasonably well done with a keyword list and some knowledge of an article being the first in a story arc (potentially to be continued as the story develops). #2 is pretty hard, as is #3 I'd be interested in throwing our polarity system against the BBC news feed to see what happens when we ignore the assumption that news articles are objective. If I have the time to do this I'll report the results here... Matt Hurst http://datamining.typepad.com On 7/18/05, Kim Plowright [EMAIL PROTECTED] wrote: its effectively spam-assassin for news, but slightly different. Wow - that's a slightly terrifying concept: the ability to filter news according to your personal preferences so you only get 'good' news delivered to you... Very 1984. *Shudder* The mood would indeed only work effectively if it leant your preferences and filtered accordingly - in effect, the current system suggests that it is 'Bad news in the eyes of right thinking people' - it would look different if the intended audience was, say, Bond Villains. Thought - wonder if a system with user-based feedback loop would be effective at catching stories that are 'spun'? Ie, cross referencing a 'mood' against the yes/no votes of the users would yield some way of spotting editorial bias, or stories that are released to sweeten potentially damaging/worrying stories with palliative good news (not necessarily by the journalists, but maybe at source)? Have you thought about running a similar 'mood detector' through video transcripts, or ficiton? It could be a useful addition to a reccomendation engine? kim -Original Message- From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] On Behalf Of Luke Dicken Sent: 18 July 2005 11:13 To: backstage@lists.bbc.co.uk Subject: RE: [backstage] Mood News 3 A really clever site would ask you for your point of view (or remember when you disagree) and adjust accordingly. A complex task though... A feedback neural network should be able to solve it reasonably straight-forwardly (although you would need a large sample of data with which to train the network on a per-user basis, which could also give large overheads) - its effectively spam-assassin for news, but slightly different. - Sent via the backstage.bbc.co.uk discussion group. To unsubscribe, please visit http://backstage.bbc.co.uk/archives/2005/01/mailing_list.html. - Sent via the backstage.bbc.co.uk discussion group. To unsubscribe, please visit http://backstage.bbc.co.uk/archives/2005/01/mailing_list.html. - Sent via the backstage.bbc.co.uk discussion group. To unsubscribe, please visit http://backstage.bbc.co.uk/archives/2005/01/mailing_list.html. - Sent via the backstage.bbc.co.uk discussion group. To unsubscribe, please visit http://backstage.bbc.co.uk/archives/2005/01/mailing_list.html.
Re: [backstage] Mood News 3
Uh, that's great, but I found this article: http://news.bbc.co.uk/1/ hi/health/4681707.stm in Bad news, when it should be good. -- Yanik Magnan On 17-Jul-05, at 5:20 PM, Davy Mitchell wrote: Hi Folks, Hope everyone had a good weekend and didn't melt! Carnoustie was HOT :-) As MN is getting a fair number of hits for its early stage in development, I have posted an update as it has moved on greatly. It's using much the same rating system. I've spent the time on reorganising the code, some DBase work, presentation and the client side stuff. Anyway... http://www.latedecember.com/sites/moodnews/ Tested on FF1.05 and IE6 on Windows Only. RSS is untested. Thanks, Davy Mitchell http://www.latedecember.com - Sent via the backstage.bbc.co.uk discussion group. To unsubscribe, please visit http://backstage.bbc.co.uk/archives/2005/01/ mailing_list.html. - Sent via the backstage.bbc.co.uk discussion group. To unsubscribe, please visit http://backstage.bbc.co.uk/archives/2005/01/mailing_list.html.
