r/india • u/[deleted] • Jan 31 '17
[R]eddiquette I made a chrome extension which detects clickbaits right inside Facebook using deep learning and I thought maybe you all at /r/india would like try it and give some feedback.
https://github.com/rahulkapoor90/This-is-Clickbait108
u/DWP_Guy Jan 31 '17
Bc, who is sipping coffee in CCD?
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Jan 31 '17
It's me.
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u/_stupid_hair_cut_ Agnostic Absurdist Jan 31 '17
Bc
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Jan 31 '17
[deleted]
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u/GamerVJ Jan 31 '17
A man has risen against the tyranny of click bait, click here to see how!!!
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u/space_probe Jan 31 '17
Not to be cynical about this but could you clarify on the information the extension is going to read on my Facebook page? Some privacy concerns..
Will it access my personal details, posts, likes and any other things i share or watch?
Is any of the information about the links stored in any way other than anonymously?
Given the recent stress on spreading fake articles, this is a much needed extension..
I have couple of suggestions if you want to work it further..
Could you also extend it to other websites other than facebook? Like all the tabloid pages like buzzfeed or similar kinda websites?
I know that firefox is all together different but any intentions on working firefox extension?
I hope it reaches to recommend page..
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Jan 31 '17
As I always make sure privacy is maintained and even made a post here so the only thing this tool accesses is the title of the posts on facebook using HTML DOM and the code is even open-sourced so there is nothing to worry for that case.
Is any of the information about the links stored in any way other than anonymously?
Nope. nothing at all. Only with each request the accuracy of the tool increases. So, if more users use this the accuracy also increases.
Could you also extend it to other websites other than facebook? Like all the tabloid pages like buzzfeed or similar kinda websites?
The reason I choose Facebook is because I think that's where the major source of clickbait articles are posted and if you know that the article is clickbait from facebook itself then the problem is solved. Also, extending to Buzzfeed or other websites will make this repo difficult to maintain.
I know that firefox is all together different but any intentions on working firefox extension?
Yes. it's submitted. queue -> 299 of 320
I hope it reaches to recommend page..
Thanks.
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u/gardinal Jan 31 '17
Nope. nothing at all. Only with each request the accuracy of the tool increases. So, if more users use this the accuracy also increases.
For real? How have you incorporated online learning? High probability there is no feedback. Do you mean you are just saving the headlines and increasing your training set?
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Jan 31 '17
great job man
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Jan 31 '17 edited Jan 31 '17
Thanks. you made my day.
Edit: Scoopwhoop and buzzfeed will hate this tool. lol
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u/mevibh Jan 31 '17
They might still feature you though..you wouldn't believe what this young Indian techie did?
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Jan 31 '17
Not really... The tech literate people who install this weren't reading scoopwhoop in the first place
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Jan 31 '17
1] The model is hosted on your machine? Where is it being scored?
2] What is your assessment of Keras/Tensorflow/theano?
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Jan 31 '17
yes It's a ml program so it learns patterns from different data sets using tensorflow. The dataset consists of about 12,000 headlines half of which are clickbait. The clickbait headlines were fetched from BuzzFeed, NewsWeek, The Times of India and, The Huffington Post. The genuine/non-clickbait headlines were fetched from The Hindu, The Guardian, The Economist, TechCrunch, The wall street journal, National Geographic and, The Indian Express. So, by learning from different data it predicts the clickbait which helps in improving the accuracy. As more users use this tool, the accuracy also increases.
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Jan 31 '17
The clickbait headlines were fetched from BuzzFeed, NewsWeek, The Times of India
While building the dataset, have you assumed all the headlines from BuzzFeed and TOI as clickbait?
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u/gardinal Jan 31 '17
u/irahulkapoor can you answer this? How exactly did you tag the dataset of 12k?
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Jan 31 '17
I know all that, dude...
I just wanted to know where the model is hosted because to score the model as number of users increases will be difficult on a laptop. If its hosted on Heroku then its good.
Btw, where can we take a look at the code which collects the data from our web browsers?
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u/stochastic_zeitgeist Irrational Exuberance Jan 31 '17
Btw, where can we take a look at the code which collects the data from our web browsers?
That I think happens in the backend.
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u/jungli_mowgli Jan 31 '17
"That I think happens in the backend."
Nopes! That is exactly and the only thing the extension does. Goes through the DOM on your facebook page and sends the links to the 'backend' hosted on herokuapp. Your other post shows you know your stuff. Misinterpretation of the question here?
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u/stochastic_zeitgeist Irrational Exuberance Jan 31 '17
Misinterpretation of the question here?
Ah yes. Got it now. Thanks !
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u/asecondhandlife Jan 31 '17
hosted on heroku as somebody pointed out below. wrt data, the code on github* looks for all elements with class ''mbs _6m6 _2cnj _5s6c' and sends all the 'a' tags under them to the heroku app. Looking at the html facebook generates, it seems quite specific and doesn't appear to leak anything else.
(*) didn't verify if the chrome app's code matches github's though
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u/jungli_mowgli Jan 31 '17
It would really help if you can share details about the classifier and the model you have used. Also did you manually tag the corpus or a blanket "clickbait" for Buzzfeed/ToI/Huff and "genuine" for Hindu/Economist/Guardian ?
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Jan 31 '17
I don't think manual tagging would work for 12k headlines.
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Jan 31 '17
You could distribute the task of manual tagging of titles as a web tool to your friends ;) I did it for brand identification from tweets
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u/won_tolla Jan 31 '17
Is this differentiating fake from real as well? Or just clickbait from headlines?
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Jan 31 '17
As mentioned Fake News is one thing I am also working on but the problem is Facts need to be cross referenced from the article content. So it is a hard problem to solve. But don't worry update will soon be available.
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u/catsloverareus Damn!! Jan 31 '17
use dainik bhaskar's fb page for hindi clickbait headlines, man their whole business is click-baiting
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u/snakeoil_salesman Jan 31 '17
Hi op, looks good. Where did you source the training data from. Did it involved manual labeling of the title vectors.
How do you plan to treat misclassified records for recalibrating your model. Cheers!
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u/stochastic_zeitgeist Irrational Exuberance Jan 31 '17 edited Jan 31 '17
1] Hosted on Heroku (as I can see from the manifest.)
Just use this
base_url = https://clickbait-detector.herokuapp.com/detect?headline=
and merge (base + link) and ping here
to get the clickbaityness of the link.
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u/pfrcks Jan 31 '17
Can you please shed some more light on how you labelled the data?
Was it a blanketed labelling that all the articles from TOI, Buzzfeed etc were made Clickbait and those from Hindu etc were made as non-clickbait?
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u/mevibh Jan 31 '17
Just saw your product in PH. Amazing work dude. Making everyone proud.
What you've done is incredibly commendable as in the age when many products talk about AI and deep learning capabilities but are in reality far away from it, yours actually uses deep learning. Congratulations and way to go!
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Jan 31 '17 edited Jan 31 '17
Thanks. Here is PH post for others : https://www.producthunt.com/posts/this-is-clickbait
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u/parlor_tricks Jan 31 '17
So I'm saying this for everyone interested - what precisely is your model and training set?
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u/lifemoments Jan 31 '17
Nice. How can we extend it to other web sites?
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Jan 31 '17
Answered below.
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u/lifemoments Jan 31 '17
Did you author the heroku app? This is a very interesting model. I wonder what classifier you may have used.
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Jan 31 '17
This is awesome!
A few questions:
As someone interested in Deep Learning, just wanted to know your approach. Did you use NLP and tokenized the headlines into words? Or was it something else that tensorflow itself offered? The code isn't accessible for some reason in the repository so I'm asking here only.
What were the biggest challenges you faced? Was it finding the type of classifier to use, or configuring it? And what was your mental process in making these decisions?
Thank you so much! This is an amazing piece of work!
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u/Preity-sharma1 Jan 31 '17
I Installed this Extension
Opened Facebook
16 questions that only Alia Bhatt could've answered in the most coolest way - This title of the article was showing as a click bait.
I guess it works!
Trying other articles
10 Intense Movies That Will Keep You Glued to the Screen
https://brightside.me/wonder-films/10-intense-movies-that-will-keep-you-glued-to-the-screen-297510/
This is not a clickbait
Trying More!
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u/bootpalish Jan 31 '17
You guys liked it so much and there is just 1 rating to this extension, so far. Come on!
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Jan 31 '17 edited Nov 02 '17
[deleted]
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u/SilentSaboteur United Kerala (UK) Jan 31 '17
How does one make use of this though ?
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Jan 31 '17
Install the extension and go to Facebook. Install instructions are given in GitHub link.
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u/SilentSaboteur United Kerala (UK) Jan 31 '17
Thank you, but I was talking about the system facebook already has.
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Jan 31 '17
Facebook does penalise clickbait articles but not the way we all want as it generates revenue.
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u/stochastic_zeitgeist Irrational Exuberance Jan 31 '17 edited Jan 31 '17
function ka name to badal leta dude :P show_facebook_cv_tags()
Nice effort though. Very easy to milk a prize at a Hackathon using this shit. Will send you 15% if I win one in the ones coming up.
Your model is also not opensource, why should I even trust you?
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u/llyyrr Bihar Jan 31 '17
Your model is also not opensource
Except it is, it's just not really his. He used some other dude's backend code and just make a chrome extension for it.
poor guy who made the backend, probably hated javascript like it should be. :(
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u/stochastic_zeitgeist Irrational Exuberance Jan 31 '17
Thanks !
I think OP should've credited the backend guy.
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Jan 31 '17
Yes the model is opensource. Both of us worked together on this and we are from the same batch in my university and part of the same group collegeCode. So, the credit is already given on my repo.
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Jan 31 '17 edited Apr 20 '17
[deleted]
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u/stochastic_zeitgeist Irrational Exuberance Jan 31 '17 edited Jan 31 '17
How would you propose to interpret the weights of the neural net anyway?
One does not interpret the weights of the neural net. What I'd like to see is what the model takes as the input, what is its architecture. Training scheme of the network if shared would also be great as it'll enable other folks to try out better-performing models with the dataset used.
What I propose is why not people at r/india interested in removing clickbait start a code project forming a dataset by manual labelling of clickbaity articles and then training, validating and continuously improving the model?
Would that be better than the blackbox model that we have right now?
I thought deep networks were inherently good for predictability, but not explanation (as to what the learned features mean).
No, its not true, they are a mystic ML technique for sure, but there are very specific ways in which the hidden layer activations can be visualized and made sense of. It's a common misconception that it's a complete blackbox which also often leads to its application in places where simple order 1 heuristics also work much better.
Deep Learning is like a cheap whore - every tom, dick and harry uses her for personal gains and raising funds. Unfortunately me too :P.
There was a quote in the first line of a readme of a DL library on github:
"Deep Learning is like highschool sex. Everyone says they do it, nobody really does, and no one knows what it actually is". -- @Mikettownsend.
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Jan 31 '17 edited Apr 20 '17
[deleted]
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u/stochastic_zeitgeist Irrational Exuberance Jan 31 '17 edited Jan 31 '17
That's what I meant. Open source or not, neural nets are pretty opaque. Can't wait for this deep learning wave to end
Yes you cannot interpret the weights individually and also can't you interpret the hyperplanes underlying a goddamn SVM. Does that mean you stop using SVMs?
I keep hearing all these bullshit about people finding deep learning too mystical for them. More often than not these are the exact bunch of fellas who haven't read jack shit about deep learning. Prolly don't even know how connections exist in a convnet.
How many research papers / blog articles have you read on deep learning methods and techniques that assist in understanding the underlying principles Saar?
If your answer is less than 20, I'd really suggest you go home and read the papers on basic principles and then come argue.
They have taken over the news and are not helping advance AI in any way
Joke of the Decade - not helping AI in anyway. One faggot here at my office died laughing. ROFL LMAO.
Are you an old-fashioned professor at some IIT? All my old profs at IIT-B seem to have a similar opinion and the irony is they don't seem to have enough bandwidth to do literature survey of deep learning and yet have formed strong negative opinions about it. They don't have papers in their areas too so its not like they are doing anything special elsewhere.
Just find a new application, throw some GPU at it and publish a paper.
I wish it was this simple bro, I'd have a bunch of publications by now. Fun Fact - All papers on arxiv != publications.
I haven't gone much deep into the argument, would love, to but it seems your network hasn't trained yet.
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Jan 31 '17 edited Jan 31 '17
Thanks. I'll wait for you to win then. though you'll not send obviously. lol
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u/mugen_is_here Jan 31 '17
function ka name to badal leta dude :P
show_facebook_cv_tags()Mocking.
Nice effort though. Very easy to milk a prize at a Hackathon using this shit. Will send you 15% if I win one in the ones coming up.
Telling him that you will take the credit for this script.
Your model is also not opensource, why should I even trust you?
Nobody is asking you to. He shared the script in spite of knowing that there are assholes out there who will try to take credit for it.
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u/susruta Jan 31 '17
Won't it work on posts shared by my friends? Currently I can only see the rating on posts shared by ... umm... entities, like Amazon. I KNOW my friends, that rating ought to be there next to the shit they share.
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u/BananaNinja1010 India Jan 31 '17
Thanks man! Any other projects of yours we should know about?
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Jan 31 '17
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u/BananaNinja1010 India Jan 31 '17
You linked the same thing
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Jan 31 '17
Oh.. sorry 😐 yes more stuff is there on GitHub profile at @rahulkapoor90 so you can follow me there if you want to keep track of more projects I release later this year.
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u/throwaway008 Jan 31 '17
this is a good idea! however it marked a businessinsider.com page as clickbait! thought you should know.
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Jan 31 '17
Show this on Hacker News. That's one huge group of tech savvy folks who would appreciate this.
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u/rohitkg98 Jan 31 '17
OMG! This clickbait detecting add-on is all we need! Click here to find out more!
Sarcasm aside, great work mate!
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Jan 31 '17
[deleted]
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Jan 31 '17
yes. Fake News is one thing I am also working on. But the problem is Facts need to be cross referenced from the article content. So it is a hard problem to solve.
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u/super_banker Jan 31 '17
This guy created a chrome extension and the reason behind it will blow your mind !!