Jennifer Shtaway, Alena Dudko, Rekha Amer, Shandiz Montazeri

Nowadays, advertisement departments and PR agencies are interested in the public response regarding their products. This is why companies such as Business Wire , NUVI, newsapi.aylien.com provide real-time social media and media monitoring and analytics.

This project will accept any user input keywords for analysis. Once a user provides a valid input, the program scans the internet via API's and webscraping to provide graphs analyzing sentiment, location, timeline of tweet among other things.

• What are the related handles (hashtags) appearing together with the user searched term?
• What is the average sentiment of top-10 influential people (with the highest number of followers) about the target term ?
• What is the average sentiment of top-10 retweets about the target term ?
• What is the overall average sentiment about the target term ?
• Which news sources write mostly about the topic?
• What is an average sentiment score of their articles? How it changes over period of time?
• How the topic popularity in media changes over period of time?

Data sets are dynamic and come from: twitter API (api.search) News API (newsapi.org) Wikipedia gmaps Google Translate

###Requirements - What you'll need in order to use this code Twitter API keys

###Python Packages tweepy, vaderSentiment, googletrans, pygeocoder, wikipedia, wordcloud, seaborn, matplotlib, pandas, numpy, BeautifulSoup

• Data retrieving, selecting and cleaning.
• Collecting and grouping data in DataFrames.
• Creating pivot tables. Calculating averages, finding highest/lowest values.
• Building charts. Analyzing findings.