As the title suggests, I want to create a filtered Twitter based on the sentiment of the tweets in my feed.
I believe I can do the first bit of obtaining the Twitter data and then running a ML model from Hugging Face. I've done that using Quix and this tutorial (https://quix.io/how-to-build-no-code-pipeline-sentiment-analysis/) But I don't know whether I have the ability to publish the feed to a web application.
Any pointers would be greatly appreciated! FYI I'm very junior!!
Related
I am building a machine learning model that would suggest attractions in a specific location.
I have most of the details worked out. However, I still need to collect the data of the attractions to train my model.
Is there somewhere I could find a dataset for this (I already checked Kaggle)? If not which websites should I scrape?
If you want to scrape data, twitter probably is the easiest to start. You can use twitter API to get any tweet that contain a specific keyword or hashtag, input your desired location as the keyword and scrape it using tweepy, i would suggest you to scrape from a specific account like Influencer or travel blog to get data about attraction.
Applying to get twitter API might take several days, and you can only scrape tweet within a time range of a weeks. older than that you need to sign up to their premium subscription.
I'm working on a application which would gather YouTube user's video data and create some meaningful data and metrics to help the creators market their videos better and expand their audience.
The problem is that since December 18, if I'm not wrong, this kind of practice is forbidden.
Can someone from Google comment and explain this change? Why can't I create metrics based on YouTube data, even if I visibly communicate that this is not data from YouTube?
For example: I would like to fetch users video description and tell what's the keyword density, how well is it prepared for SEO (in % or something).
And I guess that this new term destroys many businesses which are doing exactly that thing, creating meaningful data based on YouTube API. (Tubular, TubeBuddy, VidIQ).
Please! Anyone?
Ive searched through stack, but answers are dated. I was wondering if anyone knows what it is to crawl a topic like security. How do I do this by using Twitter? Do I just follow people who tweet about this topic, re-tweet and tweet new things, or is there an exact way of doing this? I then need to make statistical analysis on the data I gather.
You can use Puppeteer to crawl twitter data.
Checkout their github repository here.
This is a repository that crawls twitter data using Puppeteer .
How about using twitter search api (https://dev.twitter.com/docs/api/1.1/get/search/tweets)
You need to create an app first(or better say register an app) on dev.twitter.com and use search api to query for tweets that contain security (assuming I understood your crawling in the right way). Once you have your tweets you can do statistical analysis on the gathered data.
I use twitteR package on R to crawl twitter data (https://github.com/geoffjentry/twitteR) . It includes simple and useful functions to get twitter data.
I have already watched Apples's WWDC 2010 video of Building a Server-driven User Experience.
It is really a great concept but i need a simple example or tutorial to start with.
I have searched hours in Google for iOS Dynamic UI generation from XML or JSON based web services but didn't find anything useful so far.
More Information:
I am developing an iPhone application where i present user a Input Form like questionnaire with different types of question with different UI Controls to answer like Text Field, switches, image, audio, video etc.
Now I have different questionnaire for different user, I want to generate them dynamically and also store completed form in Core Data.
Any help or guidance to solve this problem will be greatly appreciated.
Thanx
have you seen heroku's Core Data Buildpack video?
http://mobile.heroku.com/
I'm currently developing a location based social network in Ruby on Rails. I also want to include a recommendation system. For testing the algorithms of this recommendations I need some real, anonymous training data. I've found the data from the Netflix Prize, but they are only including .
I'm searching for data that includes
users
friendships
locations or venues
check-ins (like in foursquare)
Does anybody know a good source for such data? Or a proven algorithm for generating this data? Or any other idea?
Search for random graph generation algorithms (more prciese, "social graph generation") to simulate social graph. Try retrieving the some test geolocation data by Google maps API or similar services. Unfortunately, I don't know what is "check-ins (like in foursquare)".
Also see Free Social Graph Data
I've finally solved it by using the gowalla API. Here you get a lot of information about users, without asking the users to permit the access to their data (kinda strange, but it works).
check it out: http://gowalla.com/api/explorer#/users/sco