CNN reports that users spend more time on Facebook than on other social networks. I could have told you that. Obviously MySpace is in 2nd place even though I don't know anyone who even uses MySpace anymore. I start to not be able to follow the article when they start listing the other social networks.
The others referenced are LinkedIn, Twitter and Blogger. LinkedIn is definitely a social network... But Twitter and Blogger? Am I confused or is the person that wrote this article or whoever did this study not really understanding what these sites do?
Showing posts with label MySpace. Show all posts
Showing posts with label MySpace. Show all posts
Tuesday, June 02, 2009
Wednesday, October 24, 2007
Yahoo 360?
- Jerry Yang shuts down Yahoo 360 and the world lets out a collective "meh."
- Translation of Yangs latest conference.
- Google finally does something about all of those horrible link farm sites that clog up its results. But they lower most blogs in the process. And another blog on the same.
- Some ibanker on "nanny arbitrage," which is where a spouse makes more money than they pay the nanny, and on how enforcing labor laws and eliminating the illegal, off-the-books, underpaid majority of nannies would have a negative impact on the legal NY labor market. From Gawker.
- iTunes removes a video starring a nude Natalie Portman. No one is sure why.
- Monetize your thirst with Facefuel. Heh.
- NY Times online meta-data.
- MySpace is still the social networking leader, although others are catching up.
- Porn may save Google $1 billion? I'm not sure how but interesting anyway. Apparently has something to do with the 2257 laws.
- Anna Nicole Smith tape. A brief exception to my ban of celebrity gossip.
- Mark Cuban finally gets the boot on the dancing show he is on. Video from Valleywag.
- Sounds like Microsoft and Facebook are finally close to closing a deal.
- Facebook is going to be rolling out "SocialAds" soon which I assume they are hoping will finally make them some money from all these eyeballs they have.
Thursday, August 23, 2007
MySpace, Facebook and Music
I was looking at the lineup for a concert and I noticed that every single band has a MySpace page as their web site. I find MySpace to be intolerably annoying and badly designed. Looking at a simple page without tons of crap on it gives me a headache, a page with all sorts of flashing banners and animations is enough to make me vomit.
Is MySpace the default way that independent musicians promote themselves now? Would having a site specialized towards musicians and not pre-teenage girls be something that people would be interested in?
I know MySpace started out as a site that a lot of musicians found useful but it has long since degenerated into a junior high school party held in a messy teenagers room.
As much as I hate Facebook at least it's clean looking. Actually I don't hate it. I just don't particularly like it. Today I was trying to join a network for a school I actually went to and I couldn't because I no longer have an email address there. It's not as user friendly as it looks, but I have to admit it does look nice. I enjoy minimalist, spare designs.
Is MySpace the default way that independent musicians promote themselves now? Would having a site specialized towards musicians and not pre-teenage girls be something that people would be interested in?
I know MySpace started out as a site that a lot of musicians found useful but it has long since degenerated into a junior high school party held in a messy teenagers room.
As much as I hate Facebook at least it's clean looking. Actually I don't hate it. I just don't particularly like it. Today I was trying to join a network for a school I actually went to and I couldn't because I no longer have an email address there. It's not as user friendly as it looks, but I have to admit it does look nice. I enjoy minimalist, spare designs.
Tuesday, August 14, 2007
Social networking and Netflix
Netflix is apparently adding some social networking / community features including:
When Netflix put out their challenge to come up with a new algorithm to recommend movies I thought about it. Being a bit of a movie buff I have some problems with their recommendations. If I said I like "Raging Bull" they would be more likely to recommend "Rocky" than "Taxi Driver" or "Mean Streets," both of which are much more similar to "Raging Bull," thematically and visually, than "Rocky" is.
My thoughts about how the recommendations should be determined was that the user needs to specify some criteria - like what they look for most in a movie. I look at the director, my wife looks at the actors. As far as I am concerned I don't care who is in a Scorsese movie because I know Scorsese will do a good job. My wife doesn't care who directs a Nic Cage movie because she likes Nic Cage. My wife is concerned with what the movie is about, I don't really care what it's about because I see movies as works of art to be experienced while she sees them as stories.
If we each said we liked the same movies Netflix would recommend the same movies to both of us, at least I think it would, while we would actually be interested in widely different films.
To account for differences like these we either need a pretty complex algorithm with lots of user-inputted data, or we need some sort of social network. Ideally would be a combination of both. People who gave similar answers to the questions as you did are likely to like similar movies as you do. Or if not you can at least see what connects the choices of the two people and make an inference based on that. This can get extremely complicated which is why I never went ahead and wrote this, although I have most of it planned out in my head.
My wife suggested that a good idea for a site would be a gift recommender. For example all of the kids out here in NY are crazy about Webkinz. Her family back in California has not heard of them. So punch in 6 year old, boy, and a location and you get customized suggestions for what such a person might like. This would obviously require a strong social component and would need to learn from the results it gives.
Anyway this Netflix idea is great. This is where the power of social networking really lies. Not in stuff like MyFacester, but in learning from crowds and applying that knowledge. This is the core of Web 2.0 in my opinion. The Wisdom of Crowds. Check out the book if you haven't already.
- Latest reviews stream that continually loads movie reviews in real time as people post them to Netflix
- “Members’ Top 10 Lists” widget that displays user-generated movie lists based on what Netflix thinks you will like
- “Unique in…” area that shows the movies that are uniquely popular in your hometown
- Selection of strangers on Netflix who share your interests or are most “similar to you”
- List of your friends’ recent activities with Netflix (what movies they have requested, whether they have been returned, etc.)
- “Friends’ Quiz” that generates simple questions to test you about your Netflix friends’ movie-renting behavior
- Friends’ Love/Hated area that shows the movies your friends loved or hated (pretty self-explanatory)
When Netflix put out their challenge to come up with a new algorithm to recommend movies I thought about it. Being a bit of a movie buff I have some problems with their recommendations. If I said I like "Raging Bull" they would be more likely to recommend "Rocky" than "Taxi Driver" or "Mean Streets," both of which are much more similar to "Raging Bull," thematically and visually, than "Rocky" is.
My thoughts about how the recommendations should be determined was that the user needs to specify some criteria - like what they look for most in a movie. I look at the director, my wife looks at the actors. As far as I am concerned I don't care who is in a Scorsese movie because I know Scorsese will do a good job. My wife doesn't care who directs a Nic Cage movie because she likes Nic Cage. My wife is concerned with what the movie is about, I don't really care what it's about because I see movies as works of art to be experienced while she sees them as stories.
If we each said we liked the same movies Netflix would recommend the same movies to both of us, at least I think it would, while we would actually be interested in widely different films.
To account for differences like these we either need a pretty complex algorithm with lots of user-inputted data, or we need some sort of social network. Ideally would be a combination of both. People who gave similar answers to the questions as you did are likely to like similar movies as you do. Or if not you can at least see what connects the choices of the two people and make an inference based on that. This can get extremely complicated which is why I never went ahead and wrote this, although I have most of it planned out in my head.
My wife suggested that a good idea for a site would be a gift recommender. For example all of the kids out here in NY are crazy about Webkinz. Her family back in California has not heard of them. So punch in 6 year old, boy, and a location and you get customized suggestions for what such a person might like. This would obviously require a strong social component and would need to learn from the results it gives.
Anyway this Netflix idea is great. This is where the power of social networking really lies. Not in stuff like MyFacester, but in learning from crowds and applying that knowledge. This is the core of Web 2.0 in my opinion. The Wisdom of Crowds. Check out the book if you haven't already.
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