We have “Like” (oneUp) button, why not “dislike” button?

facebook-dislike-button

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Last week when I was talking on Social Media Initiatives and Social Apps for Busiesses in an event, I briefly touched about how Google’s oneUp (Like) would fan into social sharing (aka networking). During the talk, a participant asked about why google did not provide “dislike”. It’s a logical question. Of course, without any inside knowledge about Google’s roadmap, I answered the question with my understanding of the field.
If you notice most of the Social Media Networks (SMN) like Facebook, Twitter, LinkedIn do not have “Dislike” button either. That too despite a huge demand. For example, there are facebook pages demanding “Dislike” button.

For example, “Facebook, give us a “dislike” button” page
http://www.facebook.com/group.php?gid=50153652583 has 493,000+ fans members.

Another page, http://www.facebook.com/pages/Make-a-Dislike-button-on-facebook/81495201767 has 25K  members.

Another interesting history about this interest in “dislike” button, last August a german company spammed SMN with its own “dislike” button as a browser plugin sounding like an official “dislike” button for Facebook. http://www.usatoday.com/tech/news/2010-08-16-facebook-dislike-fake_N.htm

Despite the popular demand, Facebook did not add “Dislike” button. Neither Google is having it. Of course, google just now launched it so we cannot be sure about its roadmap. But there are few things about Dislike button:

“Dislike” button can be used for ranking content just like “Like” button. however,

1. “Like” button tells about a preference that can be used for building a taste preference for the user and can be later used for targetted content (personalized search / offers and most importantly Ads). However, “dislike” cannot be used for targeting Ads. So from business point of view it it is not much useful.

2. “Dislike” needs a clarification: There might be many reasons of dislike and would need clarifications. So “comments” field can substitute for capturing both positive and negative feedback.

3. Technical Cost of using dislike / negative filtering is higher in delivering searches. For example, Likes can be used for matching and increasing ranking of a result based however for dislike one may need negative noise filtering.

Anyway, having said this, just because most of others do not add “Dislike”, google may not follow the same suite. We at Glomantra (myBantu.com) use both like and dislike for providing personalized relevant recommendations for the user.

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Harry Potter magic in action : Smoothly transform an image into a video

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Do you want to get experience of Harry Potter movie? Aurasma from Autonomy has something to show..

Thanks to Larry Magid for bringing this cool app to our notice via Huff post.

While it looks cool, it is not a great tech evolution in my mind. It is an innovative combination of image matching and user driven correlation of images to videos. One can tag an image and link to a video and , then any one pointing to the same image can see the magic transforming the image into the corresponding video. I am yet to have access of this to evaluate further and comment with a proper knowledge. The next step in this innovation would be if there is an automatic correlation of image to video. It would require an image to be matched with any / some video frames and then correlated without a need of tagging user.

However, even without this automatic correlation of an image to a video, the app is still a good application, especially in today’s Web2.0 world, there is an upsurge in crowd contribution in content. WikiPedia, various review sites, rating sites etc. depend on the average web user becoming a content contributor. So, if a large number of users do this tagging, this Application can find a great success. And today’s world of virality, if it catches the crowd imagination, we should see a great success story. And I would have my own contribution to it by triggering some virality via this blog entry 🙂

Its Profile Page that Facebook should worry about Not Just One-up Button

Google yesterday unveiled One-Up (+1) button on search results to indicate your liking of the result. It’s opens up a lot for Google.

1. Google can now improve the search results based on what users like. This can improve google’s aging ranking algorithm and would directly take on new entrants like Blekko who would like to provide user assisted search.

2. Google would now profile users’ liking to understand more about the user . And very soon, you may see that Google improve targeted marketing based on the users behaviour.

3. The most importantly, Google has just now threatened Facebook. Think about it. Once the usage of Profile page increases, Google would start unveiling features that would interate with videos, pictures and its emails. Slowly the Google profile would become a new Facebook. So, IMO, its the Profile Page that Facebook should worry about and not just the One-Up button.

Google Finally Added Social Search via +1 (aka Like)

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Finally Google launched a way to tag search results consumer liked. Its with +1 counter. The Liked result would be shared in the consumers social circle as well as potentially be used for public. This way, google added social concepts in its own search. Till now the concept of social search was understood as searching the social media sites for what your friend might have expressed or liked. Now, you or your friend can share the liking on the search results itself. The “liked” results would appear on consumers profile page which can be created in https://profiles.google.com/. This may look like simple but do not take it lightly over a period of time Google may expand the usage of profile page. It may add images, videos, chat, etc etc. and that would be an attack on Facebook. BTW this profile page is similar to what we have Users Profile page in myBantu. Though Google did not say how the likes would impact the search results, just like what I do in mybantu, I am sure Google would rank the liked results higher. And it would also target Blekko ‘s attempt of User’s friends assisted search, just little bit differently!