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Exploring Data Collection and Analysis Techniques Using Web Crawling and API Integration

This presentation focuses on effective tools and methods for collecting, analyzing, and modeling data from various sources, including web crawling and APIs. It discusses the evolution of input and output data handling, showcasing examples from platforms like Twitter and Facebook. The talk references influential TED talks that highlight the importance of data visualization and social network analysis. Attendees will learn about Python scripting for data extraction and transformation, as well as the differences between structured and unstructured data in the ETL process.

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Exploring Data Collection and Analysis Techniques Using Web Crawling and API Integration

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Presentation Transcript

  1. Eddie Aronovich eddiea@cs.tau.ac.il Tools presentation

  2. Once upon a time

  3. “command line” input Files Web crawling (pull) Web sensors (using API - push) “Evolution of the input”

  4. LinkedIn MAP Gapminder - http://www.ted.com/talks/hans_rosling_shows_the_best_stats_you_ve_ever_seen.html - http://www.ted.com/talks/nicholas_christakis_the_hidden_influence_of_social_networks.html Evolution of the output (multiple dimensions)

  5. Twitter • http://api.twitter.com/1/users/show.json?screen_name=TheMarker • Format the output (json) https://dev.twitter.com/docs/api/1/get/search • FB • /usr/bin/python fbconole.py fql("SELECT uidFROM user WHERE username='ariel.bardavid.5'" https://developers.facebook.com/docs/reference/apis/ API examples

  6. import json from pprint import pprint json_data=open('json_data') data = json.load(json_data) pprint(data) json_data.close() Python code for json format

  7. wget + parser (html2txt) ETL (Extract, Transform, Load) Structured vs. Unstructured data Web crawling

  8. Scripting • bash • sed • awk • cron (and scratch space) • Hadoop • Condor Some general tools

  9. Collect Data (and extract it) Analyze Data Build a model Run the model Collect more data Overview

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