Hey, everyone.
Welcome back.
So in the next project on which we are going to work up on, is it because sentiment analysis.
All right.
So in this particular project, we are going to fetch some htwe related to, let's say some particular
was so stumm and grab all those.
And we'll try to find the sentiment associated with each of those to combine the result of all those
with sentiment.
We'll try to reach some conclusion that call for some particular time.
How many negative reviews are there or overall the trends, the positives in terms of sentiment or not,
whether it's the kind of neutral or not.
So the first day wedding, which we are going to do is creating a Twitter account.
So let me go to the next step and let the search for developer.
Hopes turn it down over Twitter quicker and you can go to the very first link if you are using first
time, so you'll go apply for Texas and Britain will give you access funding.
Next is from right inside.
You can just simply see.
Get started and create your first Twitter application eventually.
Good.
And we'll give you all those token access to authenticate with the Twitter server so that we can fetch
all those a different EPA.
And it will return us to data so we can have four different option.
We are going to go with the very first one, like creating a half.
So this is already one.
I already created.
Let me create one more so that you will get idea how to create a Twitter app.
Let's see what NLB sentiment.
And here you need to write the application description.
So let me just put the same one.
Any Web site you are.
That's the request.
So I'm just going to give my.
Let's see.
Let me use it.
Let me profile.
All right.
I don't want ownable signing this Twitter account.
And these are the optional arguments, so you can easily skip it.
And Twitter is asking that.
Why and how you are going to use this step.
So this I have given how we are going to use this particular app.
So this sentiment analysis app is going to use for the two.
Dorian has one of my NLB goes a natural language processing, which spacy and whatever you can like
minimum when the character decided quite.
So let me create this particular app and you have to accept it and created.
So this app name is already being used so you can give a different name.
So let's say an LP sentiment.
Hyphen.
One, two, three, allergist's pseudonym.
And let's see whether it works or not.
All right, so now you have got creative and you can see a description, whatever we have supplied.
You can go to the key Tolkan and you can see there is already Tookey guide generated.
That is nothing with a consumer APHC and a consumer API secret key along with that.
There will be another two keys will be a access token and access to one secret that you need to generate.
All right.
So let me just copy both of them.
And let's just keep it.
Somewhere, he hopes, and that is nothing but access token and access to secret.
Apart from that, there will be EPA key EPA security, so this all keys, you're required to authenticate
yourself.
Peter Sala.
All right, so let me keep here some space.
All right.
So we got this for.
Let me executed.
And we have kept all things records in our call.
Now, when we tried to connect our patent code with this tweet, I said, what really quite all this
for talking.
You can even region that this also.
And I would highly suggest to you not to use this particular eloquence because after recording this
video, anyhow, I'm going to delete this particular rap.
You can go to permission and just make sure whether it has a lead in write permission or not.
And if you want to change the permission, you can just simply click on edit and make it a read.
And I can sleep.
And our new application like creating.
All right.
So now we have access token.
Next thing is all those required library ledgers imported.
And from the next video, we will see how to grab this data from the EPA and then.
How to find sentiment associated with those individuals.
Let me believe this, too, shall let me create fuel more then.
So to find the sentiment analysis, we are going to use one tax block library.
And that is another natural language processing library.
It is used for all those NLB related basic stuff.
And if you just supplied the text, it will give us all those sentiments associated with those text.
So we are going to use all those inbuilt CPA are available in this text block.
So from tax block, we are going to import first.
Let me connected tax block.
Let me it.
So this particular library is going to help us to find a sentiment from the tax.
Another library meeting we are going to use that is further handling Twitter API.
So that will be important to BP.
So if it is not installed, you can just simply install the flipping screen.
BP, although if you are running with this, Google will collapse and worry me.
You do not require that.
And one more thing is what we do.
But we are going to use this matplotlib.
So input matplotlib, not pipeline as yet.
All right.
So all those labels successfully got loaded.
We have all access token.
Also next video, we will see how to connect with the help of this token to the Twitter selwa.
See you in the next video.