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Super Bowl Ads on Twitter: Visualizing the Buzz

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Re: Super Bowl Ads on Twitter: Visualizing the Buzz

#2

Post by smiler »

It doesn't measure whether the tweet is positive v negative, which surely has a large impact.

I think the 'reach' figure is reaching as well, because I am guessing they just counted the number of followers the person who tweeted has, but of course, there is no way to know that every follower read that tweet.

Re: Super Bowl Ads on Twitter: Visualizing the Buzz

#3

Post by rrrazdan »

smiler wrote: post #2

It doesn't measure whether the tweet is positive v negative, which surely has a large impact. I think the 'reach' figure is reaching as well, because I am guessing they just counted the number of followers the person who tweeted has, but of course, there is no way to know that every follower read that tweet.

Its just measuring the buzz, not if it's negative or positive. In any case people talking about your ad is a good thing. Even if they say bad things, it increases your brand recall. Reach is a reasonable proxy for comparison, if you assume that ratio of people who won't(or would) see the ad, to followers is pretty much the same across ads.

Re: Super Bowl Ads on Twitter: Visualizing the Buzz

#4

Post by fvryan »

smiler wrote: post #2

It doesn't measure whether the tweet is positive v negative, which surely has a large impact. I think the 'reach' figure is reaching as well, because I am guessing they just counted the number of followers the person who tweeted has, but of course, there is no way to know that every follower read that tweet.

it's true, engagement is more important than reach.

Re: Super Bowl Ads on Twitter: Visualizing the Buzz

#5

Post by fvryan »

rrrazdan wrote: post #3
smiler wrote: post #2

It doesn't measure whether the tweet is positive v negative, which surely has a large impact. I think the 'reach' figure is reaching as well, because I am guessing they just counted the number of followers the person who tweeted has, but of course, there is no way to know that every follower read that tweet.

Its just measuring the buzz, not if it's negative or positive. In any case people talking about your ad is a good thing. Even if they say bad things, it increases your brand recall. Reach is a reasonable proxy for comparison, if you assume that ratio of people who won't(or would) see the ad, to followers is pretty much the same across ads.

Negative buzz was unlikely the goal of any of these ads. Depending on the brand it may matter more or less. Godaddy for instance has all the negative buzz they need.

Re: Super Bowl Ads on Twitter: Visualizing the Buzz

#6

Post by ims »

smiler wrote: post #2

It doesn't measure whether the tweet is positive v negative, which surely has a large impact. I think the 'reach' figure is reaching as well, because I am guessing they just counted the number of followers the person who tweeted has, but of course, there is no way to know that every follower read that tweet.

Funny you should mention it, I actually made an Android app that does basic sentiment analysis on tweets given a search term. Not very sophisticated, but it uses large corpuses assembled by text mining researchers.

Shameless plug: https://market.android.com/details?id=com.txtmine.txtminer

Re: Super Bowl Ads on Twitter: Visualizing the Buzz

#8

Post by djb_hackernews »

ims wrote: post #6
smiler wrote: post #2

It doesn't measure whether the tweet is positive v negative, which surely has a large impact. I think the 'reach' figure is reaching as well, because I am guessing they just counted the number of followers the person who tweeted has, but of course, there is no way to know that every follower read that tweet.

Funny you should mention it, I actually made an Android app that does basic sentiment analysis on tweets given a search term. Not very sophisticated, but it uses large corpuses assembled by text mining researchers. Shameless plug: https://market.android.com/details?id=com.txtmine.txtminer

How accurate is it? (Recall, Precision etc)

I was under the impression tweets are near impossible to get right to a usable degree because of how short they are on top of the usual problems of sentiment analysis.

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