This dataset is from the poll by 538 (FiveThirtyEight) that was run in 2014. The idea was to understand what Star Wars Movie responded have seen, and which is the best movie from Star Wars Franchise.

I certainly have my own favorite Star Wars movie - had it ever since I was a small kid. Let's see if American people share that opinion.

There were also questions about Star Wars Characters. Who is the most favorable and the least favorable character. Han Solo or Luke Skywalker? Let's see

https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F6808204%2F984cf944a4ef1ded058ff61d0021f394%2Fhan%20solo%20vs%20luke%20skywalker.jfif?generation=1714986135292924&alt=media" alt="">

Context

This file contains data behind the story America’s Favorite ‘Star Wars’ Movies (And Least Favorite Characters)1. The author collected the data by running a poll through SurveyMonkey Audience, surveying 1,186 respondents

Content

. The description of the questions asked in the survey is given below.

• Have you seen any of the 6 films in the Star Wars franchise?

• Do you consider yourself to be a fan of the Star Wars film franchise?

• Which of the following Star Wars films have you seen? Please select all that apply. (Star Wars: Episode I The Phantom Menace; Star Wars: Episode II Attack of the Clones; Star Wars: Episode III Revenge of the Sith; Star Wars: Episode IV A New Hope; Star Wars: Episode V The Empire Strikes Back; Star Wars: Episode VI Return of the Jedi)

• Please rank the Star Wars films in order of preference with 1 being your favorite film in the franchise and 6 being your least favorite film. (Star Wars: Episode I The Phantom Menace; Star Wars: Episode II Attack of the Clones; Star Wars: Episode III Revenge of the Sith; Star Wars: Episode IV A New Hope; Star Wars: Episode V The Empire Strikes Back; Star Wars: Episode VI Return of the Jedi)

• Please state whether you view the following characters favorably, unfavorably, or are unfamiliar with him/her. (Han Solo, Luke Skywalker, Princess Leia Organa, Anakin Skywalker, Obi Wan Kenobi, Emperor Palpatine, Darth Vader, Lando Calrissian, Boba Fett, C-3P0, R2-D2, Jar Jar Binks, Padme Amidala, Yoda)

• Which character shot first?

• Are you familiar with the Expanded Universe?

• Do you consider yourself to be a fan of the Expanded Universe?

• Do you consider yourself to be a fan of the Star Trek franchise?

• Gender

• Age

• Household Income

• Education

• Location (Census Region

Inspiration

The questions in the survey can be divided into two parts:

• One is about people’s attitude or opinion about Start War movies. • The other is about people’s demographics

Build a classifier (or some classifiers, for example one classifier per demographic feature), which can classify people’s demographics (gender, age, household income, education, location (census region)) based on their attitude or opinion about Star War movies.

Star Wars: The Old Republic player activity dataset from MMO Populations, combining monthly enhanced players and 30-day daily estimates generated from public signals.

Star Wars Galaxies: An Empire Divided player activity dataset from MMO Populations, combining monthly enhanced players and 30-day daily estimates generated from public signals.

Context

I recently saw that EA lost their exclusive rights to developing Star Wars games. This will allow other studios to develop games using the Star Wars title. I thought this subject would be interesting to look into because there has been some negative press associated with some of the games that EA has created under the Star Wars franchise. In order to see the feedback from this news, I went to reddit to grab comments associated with this news.

Content

Column Description: Author - Author of the comment Upvote - Subreddit_id - The ID of the subreddit that the comment belongs to Score - Number of upvotes Replies - This will a forest of comments starting with the top-level comment Comments - The actual comment made

I used the PRAW API that allows you to pull information from reddit. Information on the API can be found in the following location: https://praw.readthedocs.io/en/latest/index.html#

The subreddit used was: https://www.reddit.com/r/gaming/comments/kwi9yr/ea_will_no_longer_have_exclusive_rights_of_the/

Task

Determine the whether the users have a positive or negative reaction to the change in Star Wars rights associated with EA

Star-Wars-Chatbot

Simple chatbot implementation with PyTorch. A chatbot made in Python that features various data about the Star Wars universe. This is a generic chatbot. Can be trained on pretty much any conversation as long as formatted correctly JSON file. I used it for a final project in Artificial Intelligence. To use just run the script training first, then run your chatbot. For more please have a look on GitHub

Introduction

Chatbots are extremely helpful for business organizations and also the customers. The majority of people prefer to talk directly from a chatbox instead of calling service centers. Today I am going to build an exciting project on Chatbot. I will implement a chatbot from scratch that will be able to understand what the user is talking about and give an appropriate response. Chatbots are nothing but an intelligent piece of software that can interact and communicate with people just like humans. Here in this project we created an AI Chatbot which is focused for The Star Wars Cinematic Universe and trying training it in such a way that it can answer some of the basics queries about Star Wars.

Explanation Of Chatbot

Chatbots are basically AI intelligence bots which can interact with the user or customers depends upon the usage. It is an application of Artificial Intelligence and Machine Learning¬. Now-a-days technology is increasing rapidly. In this technological world every industry is trying to automate things to provide better services. One of the great application of automation would be chatbot.

There are basically two types of Chatbots :

• Command based: Chatbots that function on predefined rules and can answer to only limited queries or questions. Users need to select an option to determine their next step.
• Intelligent/AI Chatbots: Chatbots that leverage Machine Learning and Natural Language Understanding to understand the user’s language and are intelligent enough to learn from conversations with their users. You can converse via text, speech or even interact with a chatbot using graphical interfaces.

All chatbots come under the NLP (Natural Language Processing) concepts. NLP is composed of two things: - NLU (Natural Language Understanding): The ability of machines to understand human language like English. - NLG (Natural Language Generation): The ability of a machine to generate text similar to human written sentences Imagine a user asking a question to a chatbot: “Hey, what’s on the news today?” The chatbot will break down the user sentence into two things: intent and an entity. The intent for this sentence could be get_news as it refers to an action the user wants to perform. The entity tells specific details about the intent, so "today" will be the entity. So this way, a machine learning model is used to recognize the intents and entities of the chat.

Strategy

• Import Libraries and Load the Data
• Preprocessing the Data
• Create Training and Testing Data
• Training the Model
• Graphical user interface

Import Libraries and Load the Data

I created a new python file and name it as chatbot.py and then import all the required modules. After that I loaded starwarsintents.json data file in our Python program.

import numpy as np
import nltk
from nltk.stem.porter import PorterStemmer

stemmer = PorterStemmer()
import torch
import torch.nn as nn
import random
import json
from torch.utils.data import Dataset, DataLoader
from tkinter import *

with open("starwarsintents.json", "r") as f:
  intents = json.load(f)
 ```

## Preprocessing the Data

- Creating Custom Functions:

We will create custom Functions so that it is easy for us to implement afterwards. Natural language (nltk) took kit is a really useful library that contains important classes that will be useful in any of your NLP task. To know a bit more about Natural language (nltk). Please click [here](https://machinelearningmastery.com/natural-language-processing/) for more information.

- Stemming:

If we have 3 words like “walk”, “walked”, “walking”, these might seem different words but they generally have the same meaning and also have the same base form; “walk”. So, in order for our model to understand all different form of the same words we need to train our model with that form. This is called Stemming. There are different methods that we can use for stemming. Here we will use Porter Stemmer model form our NLTK Library. For more information click [here](http://snowball.tartarus.org/algorithms/porter/stemmer.html).

- Bag of Words:

We will be splitting each word in the sentences and adding it to an array. We will be using bag of words. Which will initially be a list of zeros with the size equal to the length of the all words array.If we have a array of sentences = ["hello", "how", "are", "you"] and an array of total words = ["hi", "hel...

DBPedia Classes

DBpedia is a knowledge graph extracted from Wikipedia, providing structured data about real-world entities and their relationships. DBpedia Classes are the core building blocks of this knowledge graph, representing different categories or types of entities.

Key Concepts:

Entity: A real-world object, such as a person, place, thing, or concept. Class: A group of entities that share common properties or characteristics. Instance: A specific member of a class.

Examples of DBPedia Classes:

Person: Represents individuals, e.g., "Barack Obama," "Albert Einstein." Place: Represents locations, e.g., "Paris," "Mount Everest." Organization: Represents groups, institutions, or companies, e.g., "Google," "United Nations." Event: Represents occurrences, e.g., "World Cup," "French Revolution." Artwork: Represents creative works, e.g., "Mona Lisa," "Star Wars."

Hierarchy and Relationships:

DBpedia classes often have a hierarchical structure, where subclasses inherit properties from their parent classes. For example, the class "Person" might have subclasses like "Politician," "Scientist," and "Artist."

Relationships between classes are also important. For instance, a "Person" might have a "birthPlace" relationship with a "Place," or an "Artist" might have a "hasArtwork" relationship with an "Artwork."

Applications of DBPedia Classes:

Semantic Search: DBPedia classes can be used to enhance search results by understanding the context and meaning of queries.

Knowledge Graph Construction: DBPedia classes form the foundation of knowledge graphs, which can be used for various applications like question answering, recommendation systems, and data integration.

Data Analysis: DBPedia classes can be used to analyze and extract insights from large datasets.