Learning this was a blast. Of course, anyone here should start by reading our report.
The purpose of this notebook is to use Latent Dirichlet Allocation as a method of identifying the topics of wqhich Twitter users are talking about the most.
In this section and in future work, a model will be used to identify which topics are located in each of a particular user's tweets.
Further sections of this notebook will generate User-Topic heterogenous graphs which will represent the entireity of the selec ted Twitter users and their aforementiuoned and identified topics.
Details on each piece of functionality will be outlined prior to the underlying code.
Let's begin with a bunch of import statements to gather the tools we will require.
#Data Management
import numpy as np
import pandas as pd
import json
import csv
!pip install mibian
import mibian as mb
#Topic Modelling and Data Preprocessing
import gensim
import gensim.corpora as corpora
import gensim.utils as gensim_utils
import gensim.models as gensim_models
import gensim.test.utils as gensim_test_utils
import nltk
nltk.download('stopwords')
from nltk.corpus import stopwords
import spacy
#Scikit supported on Google Colab by default
#Visualisation Toolkit
import matplotlib as plt
import networkx as nx
#MySQL
!pip install PyMySQL
import pymysql
#Twitter
!pip install python-twitter
import twitter
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Our next step is to gather the required data.
Run the following section to grab the data from Twitter. The section following this section will fetch the data via csv file input. The final Data Fetching section will parse from a publicly hosted sql server.
Yes, at one point or another during our Capstone we actually used each individual method. Here's all that code!
Input parameters for the fetched twitter data may be set below, csv file sizes and content will be inferred from Pandas.
For simplicity and continuity the final output values are identical between each input method.
#twitter_api = twitter.Api(consumer_key=[consumer key],
# consumer_secret=[consumer secret],
# access_token_key=[access token],
# access_token_secret=[access token secret])
#I'm not giving away my Entreprise keys. Get real.
from google.colab import drive
drive.mount('/content/gdrive')
Go to this URL in a browser: https://accounts.google.com/o/oauth2/auth?client_id=947318989803-6bn6qk8qdgf4n4g3pfee6491hc0brc4i.apps.googleusercontent.com&redirect_uri=urn%3Aietf%3Awg%3Aoauth%3A2.0%3Aoob&scope=email%20https%3A%2F%2Fwww.googleapis.com%2Fauth%2Fdocs.test%20https%3A%2F%2Fwww.googleapis.com%2Fauth%2Fdrive%20https%3A%2F%2Fwww.googleapis.com%2Fauth%2Fdrive.photos.readonly%20https%3A%2F%2Fwww.googleapis.com%2Fauth%2Fpeopleapi.readonly&response_type=code Enter your authorization code: ·········· Mounted at /content/gdrive
twitter_datapath = 'Tweets.csv'
users_datapath = 'Users.csv'
#NOTE: This will also work with URLs, as long as the server response is a .csv not .html
tweets_df = pd.read_csv(twitter_datapath)
print(tweets_df)
#user_id_list = tweets_df.iloc[:,3].tolist() #Grab each tweet's affiliated User
#user_id_list_string = str(user_id_list) #Cast Object to String
#user_id_tring = user_id_list_string[1:-1] #This is a mess.
#user_ids = tweets_df['UserId'] #Why not just use this? lmao
#users_df = pd.read_csv(users_datapath)
#This is to fetch User specific data (followerships, etc.) from the parsed list of users that were part of the tweet corpus.
text 0 Today is the first day of the rest of your lif... 1 This very expensive GLOBAL WARMING bullshit ha... 2 The only Forbes 5 Star & 5 Diamond hotel w... 3 Entrepreneurs are visionaries in some respects... 4 Thinking big is the driving force that has for... ... ... 12416 It was my honor to attend today’s #ArmyNavyGam... 12417 On 245 occasions former FBI Director James Co... 12418 Leakin’ James Comey must have set a record for... 12419 The Trump Administration has accomplished more... 12420 I am in the process of interviewing some reall... [12421 rows x 1 columns]
#Sample SQL Connection request
connection = pymysql.connect(host='This.Is.My.IP', user='user', password='password', db='Twitter')
#Sample SQL tweet data fetch request
tweets_df = pd.read_sql('SELECT * FROM Tweets', con=connection)
user_id_list = tweets_df.iloc[:,3].tolist()
user_id_list_string = str(user_id_list)
user_id_tring = user_id_list_string[1:-1]
#Sample SQL User data fetch via list of User IDs. User IDs provided in a variety of formats above.
#ASSUMPTION: User IDs will be attached to the tweet data that was previously fetched.
users_df = pd.read_sql(('SELECT * FROM Users WHERE Id IN ('+UserIdString+')'), con=connection)
You did it! You selected an input and the code has sucessfully run to here! You probably even see some quick tweets and users up ^there^ huh? Wicked!
Well, our data is ugly and our LDA model will just puke it right back out if we handed it over as is. We have to do some preprocessing to remove a bunch of junk and make sure that the data that's fed to the model won't cause any problems.
It's like rinsing and scraping the dishes before the dishwasher. Or maybe it's closer to giving a truck diesel and a coupe gasoline.
NOTE: Other preprocessing will be required for other aspects of the data pipeline including (but not limited to) Temporal Network Embedding, as well as Network Graph Generation methods.
def sent_to_words(sentences):
for sentence in sentences:
yield(gensim_utils.simple_preprocess(str(sentence), deacc=True))
def remove_stopwords(texts):
return [[word for word in gensim_utils.simple_preprocess(str(doc)) if word not in stop_words] for doc in texts]
def make_bigrams(texts):
return [bigram_mod[doc] for doc in texts]
def make_trigrams(texts):
return [trigram_mod[bigram_mod[doc]] for doc in texts]
def lemmatization(texts, allowed_postags=['NOUN', 'ADJ', 'VERB', 'ADV']):
"""https://spacy.io/api/annotation"""
texts_out = []
for sent in texts:
doc = nlp(u' '.join(sent))
texts_out.append([token.lemma_ for token in doc if token.pos_ in allowed_postags])
return texts_out
stop_words = stopwords.words('english')
stop_words.extend(['from', 'subject', 're', 'edu', 'use'])
data_words = list(sent_to_words(tweets_df['text'].tolist()))
bigram = gensim.models.Phrases(data_words, min_count=5, threshold=100)
trigram = gensim.models.Phrases(bigram[data_words], threshold=100)
bigram_mod = gensim.models.phrases.Phraser(bigram)
trigram_mod = gensim.models.phrases.Phraser(trigram)
nostops = remove_stopwords(data_words)
bigrams = make_bigrams(nostops)
nlp = spacy.load('en', disable=['parser', 'ner'])
data_lemmatized = lemmatization(bigrams, allowed_postags=['NOUN', 'ADJ', 'VERB', 'ADV'])
print(data_lemmatized[:1])
/usr/local/lib/python3.6/dist-packages/gensim/models/phrases.py:598: UserWarning: For a faster implementation, use the gensim.models.phrases.Phraser class
warnings.warn("For a faster implementation, use the gensim.models.phrases.Phraser class")
[['today', 'first', 'day', 'rest', 'life', 'make']]
print(data_lemmatized)
[['today', 'first', 'day', 'rest', 'life', 'make'], ['expensive', 'global_warming', 'bullshit', 'get', 'stop', 'planet', 'freezing', 'record', 'low', 'tempsand', 'scientist', 'stick', 'ice'], ['forbes', 'star', 'amp', 'diamond', 'hotel', 'star', 'diamond', 'restaurant', 'trumpnewyork', 'offer', 'elite', 'luxury', 'http', 'co', 'jkwzzruje'], ['entrepreneur', 'visionary', 'respect', 'look', 'present', 'keep', 'mind', 'look', 'opportunity'], ['think', 'big', 'driving', 'force', 'forge', 'great', 'achievement', 'modern', 'life', 'think', 'big'], ['jan', 'president', 'obama', 'end', 'vacation', 'early', 'amp', 'get', 'back', 'washington', 'straighten', 'obamacare', 'catastrophe', 'end'], ['snowden', 'come', 'back', 'america', 'face', 'justice', 'instead', 'beg', 'clemency', 'moscow', 'treat', 'spy'], ['invincibility', 'lie', 'defence', 'possibility', 'victory', 'attack', 'sun', 'tzu'], ['know', 'encourage', 'fact', 'unquestionable', 'ability', 'man', 'elevate', 'life', 'conscious', 'endeavor', 'henry', 'david', 'thoreau'], ['regular', 'part', 'day', 'devote', 'expand', 'horizon', 'learn', 'new', 'beginning'], ['try', 'develop', 'tempo', 'work', 'momentum', 'something', 'work', 'maintain', 'amp', 'important', 'element', 'success'], ['bloombergnews', 'peter', 'millard', 'trump', 'help', 'rio', 'builder', 'olympic', 'corporate', 'brazil', 'http', 'co', 'bgcaflx'], ['fundanythe', 'great', 'campaign', 'support', 'today', 'http', 'co', 'mdqpckx'], ['trumpgolfla', 'top', 'public', 'course', 'country', 'magnificent', 'pacific_ocean', 'view', 'http', 'co', 'myiwkyfivu'], ['welcome', 'new', 'obamacare', 'reality', 'doctor', 'spend', 'hour', 'hold', 'insurance', 'company', 'get', 'approval', 'surgery', 'http', 'co', 'lru', 'takz'], ['record', 'snowfall', 'amp', 'freezing', 'temp', 'country', 'global_warming', 'need'], ['future', 'always', 'begin', 'mark', 'strand', 'former', 'poet', 'laureate'], ['world', 'great', 'rider', 'today', 'trump', 'invitational', 'important', 'equestrian', 'event', 'year'], ['hit', 'facebook', 'http', 'co', 'fdv', 'aloomz'], ['timepolitic', 'zekejmiller', 'trump', 'visit', 'http', 'co', 'ydotddwcd'], ['prediction', 'come', 'true', 'iraq', 'total', 'disaster', 'government', 'lose', 'control', 'sad'], ['sec', 'state', 'kerry', 'say', 'would', 'go', 'back', 'iraq', 'say', 'stupid'], ['entrepreneur', 'set', 'example', 'magnet', 'right', 'people', 'great', 'leader', 'determine', 'team', 'assemble'], ['vision', 'amp', 'stick', 'afraid', 'unique', 'day', 'opportunity', 'show', 'highest_level'], ['experience', 'cold', 'weather', 'decade', 'people', 'never', 'remember', 'anything', 'global_warme', 'anyone'], ['looking_forward', 'hosting', 'floridagop', 'house', 'majority', 'golf', 'tournament', 'trump', 'int', 'west', 'palm_beach', 'jan'], ['congratulation', 'bretbaier', 'year', 'anniversary', 'anchor', 'specialreport', 'brett', 'great'], ['stay', 'confident', 'even', 'something', 'bad', 'happen', 'bump', 'road', 'pass', 'think', 'big'], ['achievers_move', 'forward', 'time', 'tread_water', 'get', 'go'], ['remember', 'think', 'big', 'expand', 'horizon', 'time', 'expand', 'net', 'worth'], ['identify', 'goal', 'know', 'precisely', 'want', 'achieve', 'study', 'good', 'people', 'fieldand', 'plan', 'good', 'route', 'success'], ['club', 'go', 'back', 'original', 'menu', 'preparation', 'believe', 'much', 'better', 'let', 'know', 'change', 'make'], ['critic', 'president', 'obama', 'hate', 'someone', 'robert', 'gate', 'write', 'self', 'serve', 'negative', 'book', 'boss'], ['gate', 'resign', 'unhappy', 'tell', 'obama', 'fact', 'iraq', 'always', 'disaster'], ['tomorrow', 'year', 'anniversary', 'apprentice', 'big', 'hit', 'television', 'history', 'time', 'fly'], ['great', 'year', 'macys', 'tie', 'shirt', 'suit', 'thank', 'new', 'selection', 'arrive', 'amazing'], ['paula_white', 'time', 'great', 'true', 'spiritual', 'leader', 'wonderful', 'person', 'keep', 'good', 'fight'], ['news', 'beautiful', 'miss', 'spear', 'devastating', 'know', 'spectacular', 'woman', 'miss'], ['offshore', 'wind', 'dead', 'duck', 'scotland', 'time', 'alex', 'salmond', 'man', 'stop', 'blame', 'westminster', 'cont', 'http', 'dti', 'kmitvm'], ['thank', 'everybody', 'happy_birthday', 'greeting', 'actually', 'birthday', 'apprentice', 'birthday', 'june_th'], ['foxnewslatino', 'donald', 'trump', 'plan', 'huge', 'tower', 'rio', 'post', 'olympic', 'building', 'boom', 'http', 'co', 'ijve', 'kgvfg'], ['world', 'tall', 'building', 'trumpchicago', 'star', 'hotel', 'star', 'dining_option', 'http', 'co', 'anamgudure'], ['trump', 'organization', 'continue', 'expand', 'internationally', 'record', 'pace', 'many', 'new', 'announcement', 'come', 'soon'], ['darrell', 'hammond', 'host', 'snl', 'http', 'co', 'bxsrvpr'], ['thursday', 'many', 'people', 'lose', 'healthcare', 'today'], ['still', 'believe', 'donald', 'trump', 'respond', 'tweet', 'respect', 'trump', 'would', 'good', 'pre', 'country', 'thx'], ['tough', 'smart', 'personable', 'take', 'thing', 'personally', 'good', 'business'], ['focus', 'goal', 'problem', 'problem', 'mind', 'exercise', 'learn', 'play', 'comfort', 'zone'], ['brand', 'new', 'blue_monster', 'open', 'trump', 'national_doral', 'miami', 'also', 'great', 'new', 'driving', 'range', 'open', 'midnight', 'go', 'see'], ['president', 'obama', 'fire', 'obamacare_website', 'builder', 'question', 'hire', 'first', 'place', 'sue', 'damage'], ['obamacare_website', 'contractor', 'terminate', 'obvious', 'incompetence', 'person', 'hire', 'go', 'fire'], ['politic', 'sometimes', 'life', 'friend', 'come', 'go', 'enemy', 'accumulate'], ['obama', 'bob', 'gate', 'turn', 'disloyal', 'dude', 'personally', 'hate', 'rat'], ['fox', 'amp', 'friend', 'tomorrow', 'morning', 'discussing', 'sort', 'current', 'disaster'], ['condition', 'lose', 'excuse', 'leadership', 'must', 'move', 'fast', 'decisively'], ['rodstowell', 'afraid', 'know', 'happen', 'thank'], ['watch', 'horror', 'story', 'rod', 'realize', 'time', 'let', 'pete', 'rise', 'baseball', 'hall', 'fame'], ['fox', 'amp', 'friend', 'minute', 'hope', 'enjoy'], ['helena_torry', 'consider', 'perfect', 'fault'], ['jglensteven', 'need', 'great', 'businessman'], ['anticipate', 'change', 'embrace', 'recognize', 'new', 'development', 'capitalize', 'open', 'new', 'door'], ['understand', 'difficulty', 'mistake', 'amp', 'setback', 'inevitable', 'part', 'business', 'life', 'allow', 'knock', 'foot'], ['focus', 'goal', 'fix', 'pattern', 'necessary', 'unnecessary', 'make', 'clear'], ['good', 'speech', 'goldenglobe', 'history', 'http', 'co', 'unzmbvodmo'], ['yankee', 'drop', 'rod', 'long', 'ago', 'even', 'bother', 'arbitration', 'would', 'save', 'fortune'], ['long', 'time', 'admirer', 'want', 'buy', 'book', 'friend', 'suggestion', 'art', 'deal', 'good', 'start'], ['resilience', 'part', 'survival', 'fit', 'formula', 'make', 'sure', 'remain', 'adaptable'], ['success', 'find', 'love', 'trust', 'enough', 'find', 'best', 'good'], ['great', 'success', 'need', 'passion', 'make', 'sure', 'well', 'direct', 'learn', 'everything', 'expert'], ['think', 'positively', 'negativity', 'immediately', 'focus', 'solution', 'problem', 'persistent', 'alert', 'every_single', 'day', 'momentum'], ['republican', 'must', 'change', 'culture', 'lose', 'culture', 'win', 'fast', 'last', 'decent', 'shot'], ['watch', 'gate', 'seanhannity', 'looks_like', 'get', 'hit', 'truck', 'obama', 'get', 'othersto', 'sign', 'confidentiality', 'agreement'], ['ed', 'cox', 'letter', 'republican', 'badly', 'ridicule', 'press', 'never', 'write', 'weakness', 'sad'], ['rod', 'lawsuit', 'try', 'overturn', 'bind', 'arbitration', 'agreement', 'go', 'nowhere', 'ban', 'spring', 'training'], ['gabriel', 'sherman', 'book', 'roger', 'aile', 'fill', 'falsehood', 'inaccuracie', 'publisher', 'ashamed', 'sue'], ['senate', 'immediately', 'vote', 'iranian', 'sanction', 'bill', 'delay', 'iran', 'already', 'break', 'agreement', 'obama'], ['progress', 'state', 'last', 'year', 'none', 'backwards'], ['win', 'take', 'talent', 'repeat', 'take', 'character', 'john', 'wooden'], ['would', 'like', 'thank', 'great', 'writer', 'person', 'jpappaspr', 'real_estate', 'weekly', 'wonderful', 'story', 'much', 'appreciate'], ['tedbishop', 'pga', 'thank', 'te', 'see', 'show'], ['hope', 'never', 'find', 'life', 'planet', 'doubt', 'united_states', 'start', 'send', 'money'], ['department', 'homeland_security', 'spend', 'billion_dollar', 'build', 'new', 'headquarter', 'year', 'late', 'billion', 'budget'], ['winner', 'think', 'winner', 'practice', 'positive', 'thinking', 'reality', 'check'], ['hope', 'enjoy', 'story', 'highly_respecte', 'real_estate', 'weekly', 'http', 'co', 'gbsvaf'], ['terrible', 'story', 'front_page', 'nytime', 'lightweight_agschneiderman', 'http', 'co', 'eric', 'wear', 'eyeliner'], ['lightweight_agschneiderman', 'fight', 'nygovcuomo', 'cuomo', 'win', 'easily', 'schneiderman', 'total', 'loser'], ['great', 'article', 'amspec', 'jeffrey_lord', 'reagan', 'revolution', 'realdonaldtrump', 'revolution', 'http', 'co', 'btyirbjllb'], ['looking_forward', 'host', 'saintanselm', 'politic', 'amp', 'egg', 'tuesday', 'see', 'manchester', 'nhpolitic'], ['breitbartnews', 'continue', 'push', 'limit', 'political', 'investigative', 'reporting', 'andrew', 'legacy', 'life'], ['senate', 'conclude', 'benghazi', 'could', 'prevent', 'http', 'irdr'], ['newyorkgop', 'leader', 'ed', 'cox', 'record', 'abysmal', 'victory', 'hopefully', 'turn', 'thing', 'around'], ['talent', 'win', 'game', 'teamwork', 'intelligence', 'win', 'championship', 'michael', 'jordan'], ['trust', 'instinct', 'reason', 'instinct', 'hard', 'time', 'get', 'stay', 'top'], ['get', 'momentum', 'must', 'first', 'focus', 'specific', 'goal', 'passion', 'intensity'], ['edwardfcox', 'robastorino', 'intent', 'state', 'suicide', 'mission', 'get', 'get', 'act', 'together'], ['hear', 'next', 'tuesday', 'saintanselm', 'politic', 'amp', 'egg', 'large', 'crowd', 'ever', 'looking_forward', 'make', 'new', 'friend'], ['rise', 'bay', 'street', 'trumpto', 'bring', 'opulent', 'luxury', 'famous', 'world', 'class', 'amenity', 'queen', 'city', 'http', 'co', 'cdh', 'vtd'], ['really', 'successful', 'always', 'good', 'cool', 'head', 'warm', 'heart', 'beautiful', 'common', 'touch'], ['fox', 'amp', 'friend'], ['movie', 'producer', 'harvey', 'weinstein', 'lose', 'company', 'colony', 'capital', 'gun', 'make', 'movie', 'major', 'gun', 'violence', 'really'], ['wwii', 'year', 'world', 'war', 'ii', 'start', 'japanese', 'bombing', 'pearl_harbor', 'cont', 'http', 'co', 'tyd', 'ajfpry'], ['think', 'think', 'right', 'henry_ford'], ['people', 'often', 'ask', 'secret', 'success', 'answer', 'simple', 'passion', 'focus', 'hard', 'work', 'momentum', 'keep', 'go'], ['excited', 'tomorrow', 'politic', 'amp', 'egg', 'saintanselm', 'co', 'host', 'necouncil', 'amp', 'nhiop', 'live', 'stream', 'http', 'co', 'wen', 'kbnoj'], ['hope', 'change', 'china', 'control', 'record', 'number', 'debt', 'http', 'co', 'qerjuhyulh'], ['never', 'los', 'quit', 'try', 'mike', 'ditka'], ['learn', 'expect', 'problem', 'save', 'lot', 'waste', 'energy', 'winner', 'see', 'problem', 'way', 'prove'], ['happy', 'anniversary', 'wonderful', 'wife_melaniatrump', 'truly', 'great', 'decision', 'http', 'co', 'njwv'], ['set', 'high', 'standard', 'meet', 'proof', 'learn', 'take', 'risk'], ['leave', 'palm_beach', 'ceremony', 'open', 'magnificent', 'gary_player', 'villa', 'trump', 'nationak', 'doral', 'miami', 'gary', 'great'], ['great', 'unionleader', 'piece', 'jdistaso', 'visit', 'saintanselm', 'necouncil', 'amp', 'nhiop', 'politic', 'amp', 'egg', 'http', 'co', 'cpu', 'ojrli'], ['never', 'know', 'tide', 'go', 'turn', 'favor', 'important', 'never', 'give', 'think', 'like_champion'], ['learn', 'rule', 'game', 'play', 'well', 'anyone_else', 'albert_einstein'], ['honor', 'name', 'business', 'top', 'leader', 'icon', 'rebel', 'cnbc', 'http', 'co', 'brhqcp', 'vote', 'trump'], ['great', 'day', 'yesterday', 'trumpdoral', 'unveiling', 'new', 'gary_player', 'villa', 'http', 'co', 'ajkuzlyqbg', 'gary', 'champion', 'great', 'guy'], ['story', 'midtown', 'trump', 'world', 'tower', 'glass', 'curtain', 'wall', 'true', 'landmark', 'http', 'co', 'sjcllgacdm'], ['ask', 'big', 'cast', 'announcement', 'come', 'soon', 'apprenticenbc'], ['wsj', 'wake', 'alexsalmond', 'destroy', 'scotland', 'david_cameron', 'aberdeencc', 'pressjournal', 'http', 'co', 'ofw', 'jxh'], ['time', 'difficult', 'must', 'even', 'focus', 'find', 'profitable', 'opportunity'], ['right', 'mindset', 'job', 'see', 'work', 'art', 'form', 'mean', 'pay', 'attention', 'detail'], ['news', 'call', 'great', 'freeze', 'cold', 'weather', 'year', 'country', 'still', 'spend', 'money', 'global_warming', 'hoax'], ['weather', 'event', 'use', 'global_warming', 'hoaxster', 'justify', 'high', 'taxis', 'save', 'planet', 'believe'], ['really', 'believe', 'great', 'country', 'continue', 'survive', 'incompetent', 'leadership', 'answer', 'well', 'move', 'fast'], ['fox', 'amp', 'friend', 'enjoy'], ['afghanistan', 'call', 'leader', 'karzai', 'toying'], ['give', 'goal', 'substance', 'imbue', 'value', 'exceed', 'monetary', 'make', 'count', 'many', 'level'], ['passion', 'give', 'great', 'momentum', 'catalyst', 'great', 'achievement'], ['entrepreneur', 'ignorance', 'bliss', 'fatal', 'costly', 'loser', 'get', 'organize', 'get', 'crush'], ['everything', 'come', 'hustle', 'wait', 'thomas_edison'], ['apple', 'iphone', 'sale', 'fall', 'way', 'short', 'must', 'go', 'large', 'screen', 'alternative', 'fast', 'say', 'long', 'ago', 'samsung', 'size', 'much', 'better'], ['predict', 'apple', 'stock', 'fall', 'base', 'dumb', 'refusal', 'give', 'option', 'large', 'iphone', 'screen', 'samsung', 'sell', 'apple', 'stock'], ['steve', 'job', 'spin', 'grave', 'apple', 'lose', 'vision', 'momentum', 'must', 'move', 'fast', 'get', 'magic', 'back'], ['much', 'state', 'spend', 'obnoxious', 'commercial', 'play', 'endlessly', 'tax', 'incentive', 'work'], ['smart', 'stay', 'problem', 'longer', 'albert_einstein'], ['creativity', 'control', 'go', 'hand', 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'behalf', 'flotus_melania', 'entire', 'trump', 'family', 'want', 'wish', 'merry_christma', 'may', 'christmas', 'season', 'bring', 'peace', 'heart', 'warmth', 'home', 'cheer', 'spirit', 'joy', 'world', 'nctl', 'https', 'co', 'jdsu', 'sebastian', 'gorka', 'talented', 'man', 'get', 'know', 'well', 'work', 'white_house', 'write', 'excellent', 'book', 'fight', 'much', 'learn', 'good', 'read', 'much', 'happen', 'discredit', 'witch_hunt', 'total', 'hoax', 'study', 'year', 'general_motor', 'counter', 'auto', 'company', 'big', 'steel', 'opening', 'renovate', 'plant', 'country', 'auto', 'company', 'pour', 'include', 'announce', 'major', 'new', 'plant', 'boom', 'ever', 'see', 'investigation', 'search', 'crime', 'time', 'mueller', 'angry_democrat', 'even', 'look', 'atrocious', 'perhaps', 'subversive', 'crime', 'commit', 'crooked_hillary', 'clinton', 'democrat', 'total', 'disgrace', 'illegal', 'joseph', 'mccarthy', 'style', 'witch_hunt', 'shatter', 'many', 'innocent', 'life', 'ever', 'end', 'go', 'forever', 'waste', 'possible', 'prove', 'thing', 'collusion', 'russia', 'ridiculous', 'billion', 'dollar', 'pour', 'coffer', 'tariff', 'charge', 'china', 'long', 'way', 'go', 'company', 'want', 'pay', 'tariff', 'build', 'otherwise', 'let', 'make', 'country', 'richer', 'ever', 'base', 'fact', 'ship', 'sailor', 'return', 'ukraine', 'russia', 'decide', 'would', 'good', 'party', 'concern', 'cancel', 'previously', 'schedule', 'meeting', 'argentina', 'president', 'vladimir_putin', 'look_forward', 'meaningful', 'summit', 'soon', 'situation', 'resolve', 'stevescalise', 'write', 'absolutely', 'fascinating', 'book', 'back', 'game', 'world', 'politic', 'experience', 'much', 'short', 'period', 'time', 'people', 'bravery', 'courage', 'come', 'way', 'back', 'big', 'power', 'great', 'person', 'stephenmoore', 'arthur', 'laffer', 'talented', 'man', 'complete', 'incredible', 'book', 'economic', 'policy', 'call', 'trumponomic', 'really', 'do', 'great', 'job', 'capture', 'long', 'hold', 'view', 'idea', 'book', 'sale', 'terrific', 'read', 'really', 'interesting', 'dbongino', 'new', 'book', 'spygate', 'attempt', 'sabotage', 'donald', 'trump', 'terrific', 'tough', 'smart', 'really', 'get', 'book', 'sale', 'highly', 'recommend'], ['new', 'book', 'come', 'forget', 'great', 'original', 'write', 'greggjarrett', 'judgejeanine', 'pirro', 'book', 'go', 'go', 'get', 'phony', 'witch_hunt', 'well', 'explain'], ['work', 'hard', 'go', 'get', 'well', 'https', 'co', 'mtgjmhmo'], ['rnc', 'chair', 'ronna', 'mcdaniel', 'oversaw', 'history', 'defy', 'gain', 'senate', 'unprecedented', 'fundraising', 'strength', 'ask', 'serve', 'term', 'elect', 'well', 'job'], ['land', 'argentina', 'flotus_melania', 'summit', 'https', 'co', 'zg', 'gmpazf'], ['demonstrate', 'robert_mueller', 'partisan', 'evidence', 'collusion', 'trump', 'russian', 'russian', 'project', 'legal', 'trump', 'tower', 'meeting', 'son', 'perfectly', 'legal', 'involved', 'hack', 'gregg_jarrett', 'total', 'witch_hunt'], ['alan_dershowitz', 'crime', 'mueller', 'authority', 'rove', 'commissioner', 'see', 'evidence', 'crime', 'illegal', 'hoax', 'end', 'immediately', 'mueller', 'refuse', 'look', 'real', 'crime', 'side'], ['arrive', 'argentina', 'busy', 'day', 'plan', 'important', 'meeting', 'schedule', 'great', 'country', 'extremely', 'well', 'represent', 'productive'], ['get', 'good', 'developer', 'happily', 'live', 'life', 'see', 'country', 'go', 'wrong', 'direction', 'put', 'mildly', 'odd', 'decide', 'run', 'president', 'amp', 'continue', 'run', 'business', 'legal', 'amp', 'cool', 'talk', 'campaign', 'trail'], ['lightly', 'look', 'build', 'somewhere', 'russia', 'put', 'money', 'guarantee', 'project', 'witch_hunt'], ['usmca', 'https', 'co', 'cysybybd'], ['sign', 'important', 'large', 'trade_deal', 'world', 'history', 'united_states', 'mexico', 'canada', 'work', 'well', 'together', 'craft', 'great', 'document', 'terrible', 'nafta', 'soon', 'go', 'usmca', 'fantastic'], ['great', 'people', 'alaska', 'hit', 'hard', 'big', 'follow', 'direction', 'highly_trained', 'professional', 'help', 'federal_government', 'spare', 'expense'], ['great', 'review', 'usmca', 'sooo', 'much', 'well', 'nafta'], ['great', 'day', 'summit', 'bueno', 'aire', 'argentina', 'thank', 'https', 'co', 'ihvudoygc'], ['watch', 'seanhannity', 'foxnew', 'enjoy'], ['statement', 'president', 'donald', 'trump', 'first_lady', 'melania', 'trump', 'pass', 'former', 'president', 'george_bush', 'https', 'co', 'qxpsp', 'ggs'], ['president', 'george_bush', 'lead', 'long', 'successful', 'beautiful', 'life', 'whenever', 'see', 'absolute', 'joy', 'life', 'true', 'pride', 'family', 'accomplishment', 'great', 'beginning', 'end', 'truly', 'wonderful', 'man', 'miss'], ['much', 'looking_forward', 'press_conference', 'prior', 'leave', 'argentina', 'great', 'success', 'deal', 'various', 'country', 'leader'], ['however', 'respect', 'bush', 'family', 'former', 'president', 'george_bush', 'wait', 'funeral', 'press_conference'], ['week', 'jew', 'world', 'celebrate', 'miracle', 'flotus_melania', 'send', 'bless', 'happy', 'hanukkah', 'https', 'co', 'lrngcc', 'https', 'co', 'kdjeyvkzmb'], ['china', 'agree', 'reduce', 'remove', 'tariff', 'car', 'come', 'china', 'currently', 'tariff'], ['meeting', 'china', 'extraordinary', 'relation', 'china', 'take', 'big', 'leap', 'forward', 'good', 'thing', 'happen', 'deal', 'great', 'strength', 'china', 'likewise', 'much', 'gain', 'deal', 'complete', 'level', 'field'], ['farmer', 'big', 'fast', 'beneficiary', 'deal', 'china', 'intend', 'start', 'purchase', 'agricultural', 'product', 'immediately', 'make', 'fine', 'clean', 'product', 'world', 'china', 'want', 'farmer', 'love'], ['president_xi', 'strong', 'personal', 'relationship', 'people', 'bring', 'massive', 'positive', 'change', 'trade', 'far', 'great', 'nation', 'solution', 'north_korea', 'great', 'thing', 'china'], ['certain', 'time', 'future', 'together', 'president', 'putin', 'russia', 'start', 'talk', 'meaningful', 'halt', 'become', 'major', 'uncontrollable', 'arm', 'race', 'spend', 'billion_dollar', 'year', 'crazy'], ['would', 'save', 'billion', 'dollar', 'democrat', 'would', 'give', 'vote', 'build_wall', 'way', 'people', 'allow', 'country', 'illegally', 'close', 'entire', 'southern_border', 'necessary', 'also', 'stop', 'drug'], ['michael_cohen', 'ask', 'judge', 'prison', 'time', 'mean', 'terrible', 'unrelated', 'trump', 'thing', 'fraud', 'big', 'loan', 'taxi', 'serve', 'long', 'prison', 'term', 'make', 'story', 'get', 'great', 'amp', 'already', 'reduce', 'deal', 'get'], ['wife', 'father', 'law', 'money', 'scott', 'free', 'lied', 'outcome', 'opinion', 'serve', 'full', 'complete', 'sentence'], ['never', 'testify', 'trump', 'statement', 'recently', 'make', 'roger', 'stone', 'essentially', 'state', 'force', 'rogue', 'control', 'prosecutor', 'make', 'lie', 'story', 'president', 'trump', 'nice', 'know', 'people', 'still', 'gut'], ['bob_mueller', 'much', 'different', 'man', 'people', 'think', 'control', 'band', 'angry_democrat', 'want', 'truth', 'want', 'lie', 'truth', 'bad', 'mission'], ['looking_forward', 'bush', 'family', 'pay', 'respect', 'president', 'george_bush'], ['congratulation', 'newly', 'inaugurate', 'mexican', 'president', 'lopezobrador', 'tremendous', 'political', 'victory', 'great', 'support', 'mexican', 'people', 'work', 'well', 'together', 'many', 'year', 'come'], ['remember', 'https', 'co', 'xbfylzzns'], ['looking_forward', 'wonderful', 'bush', 'family', 'blair', 'house', 'today', 'former', 'first_lady', 'come', 'white_house', 'morning', 'give', 'tour', 'christmas', 'decoration', 'melania', 'elegance', 'amp', 'precision', 'last', 'day', 'remarkable'], ['negotiation', 'china', 'already', 'start', 'extended', 'end', 'day', 'date', 'wonderful', 'warm', 'dinner', 'argentina', 'bob', 'lighthizer', 'work', 'closely', 'steve', 'mnuchin', 'larry', 'kudlow', 'wilbur', 'ross', 'peter', 'navarro'], ['see', 'real', 'deal', 'china', 'actually', 'possible', 'get', 'do', 'china', 'suppose', 'start', 'buy', 'agricultural', 'product', 'immediately', 'want', 'deal', 'happen', 'probably', 'remember'], ['tariff', 'man', 'people', 'country', 'come', 'raid', 'great', 'wealth', 'nation', 'want', 'pay', 'privilege', 'always', 'good', 'way', 'economic', 'power', 'right', 'take', 'billion', 'tariff', 'make_america', 'rich'], ['fair', 'deal', 'able', 'make', 'china', 'many', 'thing', 'know', 'must', 'finally', 'do', 'happily', 'sign', 'let', 'negotiation', 'begin', 'make_america', 'great'], ['could', 'somebody', 'explain', 'democrat', 'need', 'vote', 'country', 'loss', 'billion_dollar', 'year', 'illegal_immigration', 'include', 'terrible', 'drug', 'flow', 'top', 'border_security', 'include', 'wall', 'pay', 'month', 'get', 'do'], ['glad', 'friend', 'emmanuelmacron', 'protestor', 'paris', 'agree', 'conclusion', 'reach', 'years_ago', 'paris', 'agreement', 'fatally', 'flaw', 'raise', 'price', 'energy', 'responsible', 'country', 'whitewash', 'bad', 'polluter'], ['world', 'want', 'clean', 'air', 'clean', 'water', 'make', 'great', 'stride', 'improve', 'america', 'environment', 'american', 'taxpayer', 'american', 'worker', 'pay', 'clean', 'other', 'country', 'pollution'], ['go', 'real', 'deal', 'china', 'deal', 'point', 'charge', 'major', 'tariff', 'chinese', 'product', 'ship', 'united_state', 'ultimately', 'believe', 'make', 'deal', 'future'], ['china', 'want', 'tariff'], ['china', 'officially', 'echo', 'president', 'donald', 'trump', 'optimism', 'bilateral', 'trade', 'talk', 'chinese', 'official', 'begin', 'prepare', 'restart', 'import', 'soybean', 'amp', 'liquify', 'natural', 'gas', 'first', 'sign', 'confirm', 'claim', 'president', 'donald', 'trump', 'white_house'], ['china', 'agree', 'start', 'immediately', 'buy', 'product', 'business'], ['strong', 'signal', 'send', 'china', 'return', 'home', 'long', 'trip', 'include', 'stop', 'argentina', 'sound', 'naive', 'anything', 'believe', 'mean', 'word', 'say', 'long', 'hopefully', 'historic', 'meeting', 'subject', 'discuss'], ['exciting', 'thing', 'come', 'meet', 'china', 'promise', 'criminalize', 'sale', 'deadly', 'fentanyl', 'come', 'united_state', 'consider', 'control', 'substance', 'could', 'game', 'changer'], ['consider', 'bad', 'dangerous', 'addictive', 'deadly', 'substance', 'last', 'year', 'people', 'die', 'fentanyl', 'china', 'crack', 'horror', 'drug', 'use', 'death_penalty', 'distributor', 'pusher', 'result', 'incredible'], ['looking_forward', 'bush', 'family', 'funeral', 'day', 'celebration', 'great', 'man', 'lead', 'long', 'distinguished', 'life', 'miss'], ['hopefully', 'opec', 'keep', 'oil', 'flow', 'restrict', 'world', 'want', 'see', 'need', 'high', 'oil_price'], ['doug', 'wead', 'truly', 'great', 'presidential', 'historian', 'wonderful', 'take', 'beautiful', 'moment', 'history', 'funeral', 'service', 'today', 'president', 'bush', 'doug', 'able', 'brilliantly', 'cover', 'important', 'interesting', 'period', 'time', 'loudobbs'], ['work', 'hard', 'thank', 'https', 'co', 'sowtkzjp'], ['phony', 'russia', 'witch_hunt', 'accomplish', 'last', 'almost', 'year', 'tax', 'amp', 'regulation_cut', 'judge', 'military', 'vet', 'approval_rating', 'would', 'rather', 'report', 'rasmussen', 'call', 'presidential', 'harassment'], ['thought', 'prayer', 'usmc', 'crew', 'member', 'involve', 'mid', 'air', 'collision', 'coast', 'japan', 'thank', 'usforcesjapan', 'immediate', 'response', 'rescue', 'effort', 'need', 'iiimef'], ['fake_news', 'medium', 'ever', 'mention', 'fact', 'republican', 'important', 'help', 'campaign', 'rally', 'united_states', 'senate', 'hear', 'open', 'border', 'dem', 'house', 'senate', 'alone', 'approve', 'judge', 'amp', 'other', 'big', 'republican', 'win'], ['statement', 'china', 'team', 'side', 'smooth', 'communication', 'good', 'cooperation', 'full', 'confidence', 'agreement', 'reach', 'next', 'day', 'agree'], ['jerome', 'corsi', 'justice', 'america', 'political', 'prosecution', 'special', 'prosecutor', 'counsel', 'get', 'plea', 'deal', 'demand', 'lie', 'violate', 'law', 'criminal', 'alone', 'angry', 'dem', 'people', 'force', 'lie', 'sad', 'trish_regan'], ['trish_regan', 'fbi', 'follow', 'protocol', 'obtain', 'warrant', 'think', 'dossier', 'opposition', 'research', 'fund', 'opponent', 'government', 'resource', 'take', 'political', 'foe', 'weaponize', 'government', 'gain', 'really', 'america', 'witch_hunt'], ['fake_news', 'enemy', 'people'], ['arizona', 'together', 'military', 'border_patrol', 'bracing', 'massive', 'surge', 'non', 'walled', 'area', 'let', 'big', 'danger', 'nancy', 'chuck', 'must', 'approve', 'boarder', 'security', 'wall'], ['robert_mueller', 'leakin', 'lyin', 'good', 'friend', 'many', 'mueller', 'conflict', 'interest', 'way', 'woman', 'charge', 'prosecute', 'jerome', 'corsi', 'know', 'charge', 'legal', 'corrupt', 'clinton_foundation', 'total', 'witch_hunt'], ['robert_mueller', 'big', 'time', 'conflict', 'interest', 'list', 'top', 'republican', 'report', 'weissman', 'horrible', 'vicious', 'prosecutorial', 'past', 'list', 'report', 'wrongly', 'destroy', 'people', 'life', 'take', 'great', 'company'], ['overturn', 'united_states', 'supreme_court', 'thing', 'people', 'substantial', 'amp', 'many', 'contribution', 'make', 'angry_democrats', 'campaign', 'crooked_hillary', 'list', 'top', 'report', 'people', 'work', 'clinton'], ['foundation', 'list', 'top', 'report', 'scathe', 'document', 'write', 'lyin', 'james_comey', 'man', 'charge', 'case', 'rod', 'rosenstein', 'also', 'sign', 'warrant', 'big', 'part', 'report', 'rod', 'therefore', 'totally', 'conflict'], ['lie', 'leak', 'people', 'report', 'amp', 'also', 'lovely', 'wife', 'molly', 'comey', 'brennan', 'clapper', 'amp', 'many', 'fired', 'people', 'fbi', 'list', 'report', 'corruption', 'dnc', 'amp', 'clinton', 'campaign', 'expose', 'much'], ['china', 'talk', 'go', 'well'], ['incorrectly', 'report', 'rudy', 'giuliani', 'other', 'counter', 'mueller', 'report', 'fake_news', 'already', 'page', 'do', 'obviously', 'not', 'complete', 'see', 'final', 'witch_hunt', 'report'], ['today', 'honor', 'perish', 'pearl_harbor', 'salute', 'veteran', 'serve', 'world', 'war', 'year', 'follow', 'horrific', 'attack', 'america', 'https', 'co', 'zbu', 'https', 'co', 'hbldrqg'], ['major', 'counter', 'report', 'mueller', 'report', 'never', 'allow', 'happen', 'future', 'president', 'united_state'], ['pleased', 'announce', 'heather', 'nauert', 'spokeswoman', 'united_states', 'department', 'state', 'nominate', 'serve', 'united_nation', 'ambassador', 'want', 'congratulate', 'heather', 'thank', 'ambassador', 'nikki', 'haley', 'great', 'service', 'country'], ['pleased', 'announce', 'nominate', 'honorable', 'william', 'barr', 'position', 'attorney_general', 'united_state', 'former', 'ag', 'george_bush'], ['highly_respected', 'lawyer', 'legal', 'mind', 'country', 'great', 'addition', 'team', 'look_forward', 'join', 'successful', 'administration'], ['mike_pompeo', 'great', 'job', 'proud', 'predecessor', 'mental', 'capacity', 'need', 'dumb', 'rock', 'fast', 'enough', 'lazy', 'hell', 'whole', 'new', 'ballgame', 'great', 'spirit', 'state'], ['hopefully', 'mitch_mcconnell', 'ask', 'vote', 'criminal', 'justice', 'reform', 'extremely', 'popular', 'strong', 'bipartisan', 'support', 'also', 'help', 'lot', 'people', 'save', 'taxpayer', 'dollar', 'keep', 'community', 'safe', 'go', 'mitch'], ['report', 'leakin', 'tell', 'department', 'justice', 'attorney', 'answer', 'important', 'question', 'total', 'bias', 'corruption', 'high', 'level', 'previous', 'administration', 'force', 'answer', 'question', 'oath'], ['totally', 'clear', 'president', 'thank'], ['paris', 'agreement', 'work', 'well', 'pari', 'protest', 'riot', 'france', 'people', 'want', 'pay', 'large', 'sum', 'money', 'much', 'third', 'world', 'country', 'questionably', 'run', 'order', 'maybe', 'protect', 'environment', 'chant', 'want', 'trump', 'love', 'france'], ['idea', 'european', 'military', 'work', 'well', 'always', 'ask', 'pay', 'fair', 'share', 'nato', 'germany', 'pay', 'pay', 'much', 'large', 'gdp', 'protect', 'europe', 'fairness'], ['year', 'million', 'page', 'document', 'cost', 'collusion'], ['pleased', 'announce', 'nomination', 'star', 'general', 'mark', 'milley', 'chief', 'staff', 'united_states', 'army', 'chairman', 'joint', 'chief', 'staff', 'replace', 'general', 'joe', 'dunford', 'retiring'], ['thankful', 'incredible', 'man', 'service', 'country', 'date', 'transition', 'determine'], ['collusion', 'illusion', 'smoking', 'gun', 'late', 'date', 'go', 'million', 'spend', 'russian_collusion', 'nothing', 'impeachable', 'geraldorivera', 'time', 'witch_hunt', 'end'], ['sad', 'day', 'amp', 'night', 'pari', 'maybe', 'time', 'end', 'ridiculous', 'extremely', 'expensive', 'paris', 'agreement', 'return', 'money', 'back', 'people', 'form', 'lower_taxe', 'way', 'ahead', 'curve', 'major', 'country', 'emission', 'go', 'last', 'year'], ['watch', 'dick', 'blumenthal', 'television', 'spew', 'fact', 'almost', 'accurate', 'bravery', 'vietnam', 'never', 'see', 'bullet', 'whiz', 'dick', 'head', 'save', 'soldier'], ['leave', 'right', 'woke', 'dream', 'scream', 'lie', 'next', 'time', 'go', 'vietnam', 'ask', 'dick', 'travel'], ['great', 'honor', 'head', 'army', 'navy', 'game', 'today', 'shortly', 'land', 'https', 'co', 'byafesq'], ['armynavygame', 'https', 'co', 'yjhq'], ['honor', 'attend', 'today', 'armynavygame', 'philadelphia', 'great', 'game', 'play', 'hero', 'congratulation', 'armywp_football', 'win', 'https', 'co', 'wdlkm'], ['occasion', 'former', 'fbi', 'director', 'tell', 'house', 'investigator', 'know', 'recall', 'remember', 'thing', 'ask', 'open', 'investigation', 'american', 'know', 'sign', 'know', 'lie'], ['leakin', 'must', 'set', 'record', 'lie', 'congress', 'day', 'friday', 'testimony', 'untruthful', 'whole', 'deal', 'rig', 'fraud', 'head', 'dishonest', 'people', 'would', 'anything', 'could', 'become', 'president', 'expose'], ['trump', 'administration', 'accomplish', 'administration', 'first', 'even', 'year', 'existence', 'amp', 'great', 'time', 'fake_news', 'medium', 'go', 'totally', 'mind', 'truly', 'enemy', 'people'], ['process', 'interview', 'really', 'great', 'people', 'position', 'white_house', 'chief', 'staff', 'fake_news', 'say', 'certainty', 'nick', 'ayer', 'spectacular', 'person', 'always', 'maga', 'agenda', 'make', 'decision', 'soon']]
NOTE: Later sections implement the utlization of previously created LDA Models, or the import of Topics and Concepts via SQL/.csv.
Amazing! We're now prepared our data to be interpretted by our data science toolkits.
In the following section we will now develop the LDA Topic Model that will late rbe used to identify which topics are affiliated with which tweets, and therefore users.
We're gonna train our model using the entirety of the tweets we're pulled from our original data import as a corpus.
Additional input arguments may be set manually, but the default matches the previous work's parameters.
id2word = corpora.Dictionary(data_lemmatized) #Lemmatized corpus for identifying terms
texts = data_lemmatized #Style points.
corpus = [id2word.doc2bow(text) for text in texts] #Each individual term in our corpus
[[(id2word[id], freq) for id, freq in cp] for cp in corpus[:1]] #Fetch and assigned the frequency of each term in our corpus.
lda_model = gensim.models.ldamodel.LdaModel(corpus=corpus,
id2word=id2word,
num_topics=50, #Let's grab 50 topics.
random_state=100,
update_every=1,
chunksize=100,
passes=10,
alpha='auto',
per_word_topics=True)
#LDA_Model has been made!
doc_lda = lda_model[corpus]
#Let's see what some of these topics looks like.
topic_array = lda_model.get_topics()
topic_term_array = lda_model.get_topic_terms(2)
print(topic_array)
print(topic_term_array)
Now that we have model built to evaluate the content of each tweet, we will asssign topics to users.
user_topic_edges = []
#For each lemmatized tweet:
ind = 0;
for doc in data_lemmatized:
q_vec = id2word.doc2bow(doc)
#pprint(q_vec)
#Fetch the topic of each tweet, in order to pair Topics to UserIDs.
topic_vec = lda_model.get_document_topics(q_vec)
topic_prob = 0;
topic_id = -1;
for pair in topic_vec:
prob = pair[1]
id = pair[0]
if prob > topic_prob:
topic_prob = prob
topic_id = id
#pprint(topic_vec)
user_id = UserIdList[ind]
user_topic_edges.append((topic_id, user_id))
ind = ind + 1;
Now that we have model built to evaluate the content of each tweet, we will asssign topics to topics.
This allows us to later use things like clustering to idetify similar or groups of topics. (Ex/ Golf, Tennis and Hockey all fall within a parent topic; Sports.)
# wikirelate was here
topicModel = Word2Vec.load_word2vec_format('Values.bin.gz', binary=True) #https://www.aaai.org/Papers/AAAI/2006/AAAI06-223.pdf
#This is a previously built topic-relatedness model using Word2Vec and Wikirelate.
tsg = nx.Graph()
topic_topic_edges = []
int t = 0;
for topic in ndarray #We're gonna pair all topics together
#This isn't what a Try/Catch is for, dummy. This is embarassing. You're better than this.
try:
topicTermsA = lda_model.show_topic(t)
topicTermsB = lad_model.show_topic(t + 1)
distance = topicModel.wmdistance(topicTermsA, topicsTermsB)
pprint(distance)
tempEdge = (t, t + 1, {'weight':distance}) #Weighted distancing based on topic relatedness.
topic_topic_edges.append(tempEdge)
except:
#Pathetic.
print("End of Topics!")
# We made it here, we can go anywhere
# "Don't put song lyrics in the comments." -Ron, ...probably
G = nx.Graph()
G.add_nodes_from(UserIdList)
G.add_edges_from(user_topic_edges)
nx.draw(G)
plt.show()
nx.write_edgelist(G, "test1.edgelist", data=True)
graphJSONData = nx.readwrite.node_link_data(G)
#May need to move json
#import json
with open('data.json', 'w') as outfile:
json.dump(data, outfile)
vis = pyLDAvis.gensim.prepare(lda_model, corpus, id2word)
pyLDAvis.save_html(vis, 'Export_LDA_Visualization.html')
These network graphs would serve as the basis fora prediction model. Temporal Link Prediction models were used to link users to each others communities, essentially predicting their next interest/topic.
Temporal Link Prediction Paper 1
Temporal Link Prediction Paper 2
Temporal Prediction Model GitHub
Once that was completed, the model was tuned using an AUROC to determine best fit. You can read the full results of our project in the report.