{"id":13338870,"url":"https://github.com/triandicAnt/TwitterSentimentAnalytics","last_synced_at":"2025-03-11T10:32:13.112Z","repository":{"id":67655430,"uuid":"56082234","full_name":"triandicAnt/TwitterSentimentAnalytics","owner":"triandicAnt","description":"Basic Twitter Sentiment Analytics using Apache Spark Streaming APIs and Python by processing live tweets from Twitter.","archived":false,"fork":false,"pushed_at":"2016-10-24T02:03:22.000Z","size":2446,"stargazers_count":2,"open_issues_count":0,"forks_count":3,"subscribers_count":2,"default_branch":"master","last_synced_at":"2024-10-23T22:20:08.950Z","etag":null,"topics":["machine-learning","python","sentimental-analysis","spark","twitter","twitter-api","twitter-sentiment-analytics"],"latest_commit_sha":null,"homepage":"","language":"Java","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/triandicAnt.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2016-04-12T17:04:07.000Z","updated_at":"2021-11-10T23:53:50.000Z","dependencies_parsed_at":"2023-06-10T09:31:03.406Z","dependency_job_id":null,"html_url":"https://github.com/triandicAnt/TwitterSentimentAnalytics","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/triandicAnt%2FTwitterSentimentAnalytics","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/triandicAnt%2FTwitterSentimentAnalytics/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/triandicAnt%2FTwitterSentimentAnalytics/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/triandicAnt%2FTwitterSentimentAnalytics/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/triandicAnt","download_url":"https://codeload.github.com/triandicAnt/TwitterSentimentAnalytics/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":243015509,"owners_count":20222089,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["machine-learning","python","sentimental-analysis","spark","twitter","twitter-api","twitter-sentiment-analytics"],"created_at":"2024-07-29T19:17:52.608Z","updated_at":"2025-03-11T10:32:13.099Z","avatar_url":"https://github.com/triandicAnt.png","language":"Java","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Twitter-Sentiment-Analytics\nBasic Twitter Sentiment Analytics using Apache Spark Streaming APIs and Python by processing live tweets from Twitter.\n\n### Objectives:\n* Perform Sentiment Analysis over live-streaming tweets from Twitter using Twitter API and Apache Spark. \n* Using Apache Kafka to buffer live tweets data fetched with help of Twitter API.\n* Using stream processing API provided by Spark convert the live data to DStreams and classify each as positive and negative.\n* Plot the variation of word counts with respect to time period using python's MatPlotLib.\n* Data-set for positive and negative words were static text files each consisting 3000+ words.\n\n### Steps:\n```\n1. #Start zookeeper\nbin/zookeeper-server-start.sh config/zookeeper.properties\n\n      #stop zookeeper\n      sudo service zookeeper stop\n\n2. #start kafka server\nbin/kafka-server-start.sh config/server.properties\n\n3. # create a topic\nbin/kafka-topics.sh --create --zookeeper localhost:2181 --replication-factor 1 --partitions 1 --topic twitterstream\n\n4. # list all topics\nbin/kafka-topics.sh --list --zookeeper localhost:2181\n\n5. # Provide twitter credentials without quote in twitter.txt\n\n6. #start streaming twitter data\npython twitter_to_kafka.py\n\n7. #check streamed data\nbin/kafka-console-consumer.sh --zookeeper localhost:2181 --topic twitterstream --from-beginning\n\n8. #do sentiment analysis on data\n$SPARK_HOME/bin/spark-submit --packages org.apache.spark:spark-streaming-kafka_2.10:1.5.1 twitterStream.py\n```\n### Sample Date\n```\nTONIGHT IS A NIGHTMARE\nWho needs therapy after this episode #TheWalkingDead \n\n🙋🏻🙋🏼🙋🏽🙋🙋🏾🙋🏻🙋🏼🙋🏾🙋🏽🙋🏻🙋🏼🙋🏾🙋🏽🙋🏻🙋🏼🙋🏾🙋🏽🙋🏻🙋🏼🙋🏾🙋🏽🙋🏻🙋🏼🙋🏾🙋🏽🙋🏻🙋🏼🙋🏾🙋🏽🙋🏻🙋🏼🙋🏾🙋🏽\nI bet we know who everyone will be for #Halloween #Negan #Lucille #TheWalkingDead https://t.co/p4lBeuLSxZ\nOkay but honestly... Jim would vote for Trump, right?\nNo matter how many times we fight you're my bestfriend and no matter what I will stop and listen to you. Dont forget that.\nThe tables will turn. #TheWalkingDead\n@SydneyKoolstra and I have decided to involve our selves in what @10_shelby_10 is for Halloween. Choose wisely.\n@ABC how does one actually offend a pornstar, that's not possible\nYeah fuck you negan #TheWalkingDead\nI liked him tooo BUT BRUHHH\nHow's my little skunk butt already 2 months old😭😭😭 Auntie mo needs you to stop growing up so quick😭🐒💕 https://t.co/IIesieiS6B\nImma have to smoke now instead of am cause im in bad mood\nThat axe is gona play a huge role this season #TheWalkingDead\n#TheWalkingDead thought this show was about zombies 😭😭😭😭😭 wtf\n🌹👁🌹🙏🏾BLESSED EVENING EVERYONE BE SAFE AND ENJOY FOLLOW THE CHOO CHOO🚂💨🌹👁🌹💯@TAMMYYO86840808 @_Mr_Clutch_3… https://t.co/IcIfU3Agqw\nFinally watching Hocus Pocus ☺️🎃🎃\n@jayhamilton87 would've been quite the player\nHow they had us wondering if Glenn was dead or alive and then still kill him? smh  #TheWalkingDead\n@TylerSimi 😂😂😂 lol you're the best. thank you silly\nThanks to Prague, I now have my 10th tattoo. Also thanks to Prague, it's 3 am and I am doing homework.\n@kevinmelrose94 thank you Aaron!\nRobbery | Maple Leaf Dr \u0026amp; Jane St Black Cr S Ramp [12 Div.] 10/23 21:53 #Toronto_Division\nWhat about classy ? I only het hood when needed too 😂 https://t.co/1rLHASZBN1\nyou're the sweetest. 😭❤️ miss you! https://t.co/frnFvXaYnd\nThanks Cubs! #cubswin #eiuhomecoming2016 @ Eastern Illinois University https://t.co/NQbOxZaWTG\nI drop off chase then we immediately get on FaceTime..\nAfter so many years of #TheWalkingDead I just don't think I can watch this show anymore.\n@HBfromKC I'm so sorry. I'll behave.\nOMG! I honestly don't even know my current emotional state right now... #TheWalkingDead\nIf you know you couldn't do anything tonight, why wouldn't you say that from the jump?? 🙄\n```\n### Sentiment Plot:\n\nPlot between positive and negative words in a time frame:\n\n![alt text](https://github.com/sudhansusingh22/Twitter-Sentiment-Analytics/blob/master/plot.png \"Sentiment Plot\")\n\n\n\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2FtriandicAnt%2FTwitterSentimentAnalytics","html_url":"https://awesome.ecosyste.ms/projects/github.com%2FtriandicAnt%2FTwitterSentimentAnalytics","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2FtriandicAnt%2FTwitterSentimentAnalytics/lists"}