StormTweetsSentimentD3Viz | sentiment analysis of tweets of US States | Predictive Analytics library

 by   P7h Java Version: Current License: Apache-2.0

kandi X-RAY | StormTweetsSentimentD3Viz Summary

kandi X-RAY | StormTweetsSentimentD3Viz Summary

StormTweetsSentimentD3Viz is a Java library typically used in Telecommunications, Media, Media, Entertainment, Analytics, Predictive Analytics applications. StormTweetsSentimentD3Viz has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can download it from GitHub, GitLab.

This repository contains an application which is built to demonstrate as an example of Apache Storm distributed framework by performing sentiment analysis of tweets originating from U.S. in real-time. This Topology retrieves tweets originating from US and computes and visualizes the sentiment scores of each of the state of United States [based on tweets] in a Choropleth Map using D3.js continuously for 10 minutes [in local mode]. User can also explicitly kill the topology by pressing Ctrl+C for exiting the application. Also, there is a column chart visualization of each State and its sentiment value using Highcharts. Apache Storm is an open source distributed real-time computation system, developed at BackType by Nathan Marz and team. It has been open sourced by Twitter [post BackType acquisition] in August, 2011. And Storm became a top level project in Apache on 29th September, 2014. This application has been developed and tested with Storm v0.8.2 on Windows 7 in local mode; and was eventually updated and tested with Storm v0.9.3 on 05th January, 2014. Application may or may not work with earlier or later versions than Storm v0.9.3.

            kandi-support Support

              StormTweetsSentimentD3Viz has a low active ecosystem.
              It has 26 star(s) with 24 fork(s). There are 7 watchers for this library.
              It had no major release in the last 6 months.
              StormTweetsSentimentD3Viz has no issues reported. There are no pull requests.
              It has a neutral sentiment in the developer community.
              The latest version of StormTweetsSentimentD3Viz is current.

            kandi-Quality Quality

              StormTweetsSentimentD3Viz has 0 bugs and 0 code smells.

            kandi-Security Security

              StormTweetsSentimentD3Viz has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
              StormTweetsSentimentD3Viz code analysis shows 0 unresolved vulnerabilities.
              There are 0 security hotspots that need review.

            kandi-License License

              StormTweetsSentimentD3Viz is licensed under the Apache-2.0 License. This license is Permissive.
              Permissive licenses have the least restrictions, and you can use them in most projects.

            kandi-Reuse Reuse

              StormTweetsSentimentD3Viz releases are not available. You will need to build from source code and install.
              Build file is available. You can build the component from source.
              Installation instructions are not available. Examples and code snippets are available.
              StormTweetsSentimentD3Viz saves you 741 person hours of effort in developing the same functionality from scratch.
              It has 1709 lines of code, 38 functions and 18 files.
              It has medium code complexity. Code complexity directly impacts maintainability of the code.

            Top functions reviewed by kandi - BETA

            kandi has reviewed StormTweetsSentimentD3Viz and discovered the below as its top functions. This is intended to give you an instant insight into StormTweetsSentimentD3Viz implemented functionality, and help decide if they suit your requirements.
            • Processes a single tweet
            • Reverse the status of a given Latitude and longitude
            • Get the state of the tweet
            • Get the state of a Tweet
            • Retrieves the state of the user from a user object
            • Get the state of a tweet
            • Get the state of a Tweet from a GeoLocation object
            • Process a tweet
            • Get the sentiment of a tweet
            • Declares the output fields
            • Cleans up resources
            • Get the next tuple from the pipeline
            • Main entry point
            • Opens the Spider
            • Demonstrates how to use the Google Maps API
            • Process a tuple
            • Initializes the state locator
            • Removes the URLs from a tweet
            • Reads the information from the file and stores them in a map
            • Declare the output fields
            Get all kandi verified functions for this library.

            StormTweetsSentimentD3Viz Key Features

            No Key Features are available at this moment for StormTweetsSentimentD3Viz.

            StormTweetsSentimentD3Viz Examples and Code Snippets

            No Code Snippets are available at this moment for StormTweetsSentimentD3Viz.

            Community Discussions


            will TensorFlow utilize GPU for predictive Analysis?
            Asked 2020-Nov-21 at 21:35

            GPU is good for parallel computing but the problem is some machine learning libraries don't utilize the GPU, unless that machine learning based on image processing or some sort of graphics processing, what if I am using machine learning for predictive Analytics? do libraries like TensorFlow utilize the GPU? or they use only CPU? or can I choose which processing unit to use? whats the deal here?

            note: predictive Analysis requires no graphics processing.



            Answered 2020-Nov-21 at 21:35
            The short answer: yes, it will! The slightly longer answer:

            The computation that happens in the GPU in any of the machine learning frameworks that support GPUs is not limited to graphical processing. For instance, if your model is a simple logistic regression, a framework such as TensorFlow will run it on the GPU if properly configured.

            The advantage of GPUs for machine learning is that training big neural networks benefits greatly from the high level of parallelism that the GPUs offer.

            If you want to know more about this, I'd recommend you start here or here.

            some things to consider:
            • how much a model will benefit from running in the GPU will depend on how much it will benefit from parallel computation in general.
            • Deep Learning models can be applied to predictive analytics, as well as more classical machine learning models. Bear in mind that neural nets are possibly the category of models that will benefit inherently from the GPU (see links above).
            • Even though running models using GPUs (or even more specialised hardware) can bring benefits, I would suggest that you don't choose a framework and, especially, don't choose an algorithm based solely on the fact that it will benefit from parallelism, but rather look at how appropriate a given algorithm is for the data you have.



            Restructuring Pandas Dataframe for large number of columns
            Asked 2020-Nov-01 at 19:39

            I have a pandas dataframe which is a large number of answers given by users in response to a survey and I need to re-structure it. There are up to 105 questions asked each year, but I only need maybe 20 of them.

            The current structure is as below.

            What I want to do is re-structure it so that the row values become column names and the answer given by the user is then the value in that column. In a picture (from Excel), what I want is the below (I know I'll need to re-name my columns, but that's fine once I can create the structure in the first place):

            Is it possible to re-structure my dataframe this way? The outcome of this is to use some predictive analytics to predict a target variable, so I need to re-strcture before I can use Random Forest, kNN, and so on.



            Answered 2020-Nov-01 at 19:39

            You might want try pivoting your table:



            Display data from two json files in react native
            Asked 2020-May-17 at 23:55

            I have js files Dashboard and Adverts. I managed to get Dashboard to list the information in one json file (advertisers), but when clicking on an advertiser I want it to navigate to a separate page that will display some data (Say title and text) from the second json file (productadverts). I can't get it to work. Below is the code for the Dashboard and next for Adverts. Then the json files



            Answered 2020-May-17 at 23:55

            The new object to get params in React Navigation 5 is:


            Community Discussions, Code Snippets contain sources that include Stack Exchange Network


            No vulnerabilities reported

            Install StormTweetsSentimentD3Viz

            You can download it from GitHub, GitLab.
            You can use StormTweetsSentimentD3Viz like any standard Java library. Please include the the jar files in your classpath. You can also use any IDE and you can run and debug the StormTweetsSentimentD3Viz component as you would do with any other Java program. Best practice is to use a build tool that supports dependency management such as Maven or Gradle. For Maven installation, please refer For Gradle installation, please refer .


            For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .
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