About this Course
최근 조회 12,671

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지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.

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중급 단계

완료하는 데 약 14시간 필요

권장: 4 weeks of study, 3-6 hours/week...

영어

자막: 영어

귀하가 습득할 기술

Python ProgrammingStatistical AnalysisSentiment AnalysisR Programming

100% 온라인

지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.

유동적 마감일

일정에 따라 마감일을 재설정합니다.

중급 단계

완료하는 데 약 14시간 필요

권장: 4 weeks of study, 3-6 hours/week...

영어

자막: 영어

강의 계획 - 이 강좌에서 배울 내용

1
완료하는 데 3시간 필요

Introduction to Data Analytics

In this first unit of the course, several concepts related to social media data and data analytics are introduced. We start by first discussing two kinds of data - structured and unstructured. Then look at how structured data, the primary focus of this course, is analyzed and what one could gain by doing such analysis. Finally, we briefly cover some of the visualizations for exploring and presenting data.Make sure to go through the material for this unit in the sequence it's provided. First, watch the four short videos, then take the practice test, followed by the two quizzes. Finally, read the documents about installation and configuration of Python and R. This is very important - before proceeding to the next units, make sure you have installed necessary tools, and also learned how to install new packages/libraries for them. The course expects students to have programming experience in Python and R.

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4 videos (Total 33 min), 4 readings, 2 quizzes
4개의 읽기 자료
Anaconda Installation20m
Python installation, configuration, and usage30m
R installation30m
R/RStudio Setup Guide (on Windows)20m
2개 연습문제
Quiz-115m
Quiz-215m
2
완료하는 데 4시간 필요

Collecting and Extracting Social Media Data

In this unit we will see how to collect data from Twitter and YouTube. The unit will start with an introduction to Python programming. Then we will use a Python script, with a little editing, to extract data from Twitter. A similar exercise will then be done with YouTube. In both the cases, we will also see how to create developer accounts and what information to obtain to use the data collection APIs. Once again, make sure to go item-by-item in the order provided. Before beginning this unit, ensure that you have all the right tools (Python, R, Anaconda) ready and configured. The lessons depend on them and also your ability to install required packages.

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4 videos (Total 47 min), 6 readings, 3 quizzes
4개의 동영상
Video-4: Using Python to Extract Data from YouTube11m
6개의 읽기 자료
Errata: please read this first1m
Python Packages Installation5m
(Optional) Introduction to Python for Econometrics, Statistics and Data Analysis30m
Script: twitter_search.py
Twitter libraries10m
Script: youtube_search.py
2개 연습문제
Python Programming Exercise2m
YouTube data download using Python6m
3
완료하는 데 4시간 필요

Data Analysis, Visualization, and Exploration

In this unit, we will focus on analyzing and visualizing the data from various social media services. We will first use the data collected before from YouTube to do various statistics analyses such as correlation and regression. We will then introduce R - a platform for doing statistical analysis. Using R, then we will analyze a much larger dataset obtained from Yelp. Make sure you have covered the material in the previous units before proceeding with this. That means, having all the tools (Anaconda, Python, and R) as well as various packages installed. We will also need new packages this time, so make sure you know how to install them to your Python or R. If needed, please review some basic concepts in statistics - specifically, correlation and regression - before or during working on this unit.

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4 videos (Total 87 min), 8 readings, 2 quizzes
4개의 동영상
Video-4: Social Media Data Analysis with R32m
8개의 읽기 자료
Script: twitter_process.py
Data: iqsize.csv
R Installation Guide10m
Installing R Packages5m
Statistical Analysis with R10m
Read this first2m
Scripts for converting json to csv2m
Data Visualization with ggplot2 (R) - Cheat Sheet10m
1개 연습문제
Statistical Analysis with Twitter Data6m
4
완료하는 데 3시간 필요

Case Studies

In the final unit of this course, we will work on two case studies - both using Twitter and focusing on unstructured data (in this case, text). The first case study will involve doing sentiment analysis with Python. The second case study will take us through basic text mining application using R. We wrap up the unit with a conclusion of what we did in this course and where to go next for further learning and exploration.

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4 videos (Total 47 min), 4 readings, 2 quizzes
4개의 읽기 자료
Script: twitter_sentiments.py
NLTK10m
Script: text_mining_twitter.r
An Introduction to Network Analysis with R and statnet10m
1개 연습문제
Sentiment Analysis with Twitter6m
4.1
31개의 리뷰Chevron Right

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이 강좌를 통해 확실한 경력상 이점 얻기

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Social Media Data Analytics의 최상위 리뷰

대학: AMMay 10th 2018

Instructor was great, deliver lectures really nice. Looking for some more stuff from Dr. Shah

대학: MIFeb 7th 2019

very nice couse but peer assignment is very difficult taks

강사

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Chirag Shah

Associate Professor
Information and Computer Science

러트거스 뉴저지 주립 대학교 정보

자주 묻는 질문

  • 강좌에 등록하면 바로 모든 비디오, 테스트 및 프로그래밍 과제(해당하는 경우)에 접근할 수 있습니다. 상호 첨삭 과제는 이 세션이 시작된 경우에만 제출하고 검토할 수 있습니다. 강좌를 구매하지 않고 살펴보기만 하면 특정 과제에 접근하지 못할 수 있습니다.

  • 수료증을 구매하면 성적 평가 과제를 포함한 모든 강좌 자료에 접근할 수 있습니다. 강좌를 완료하면 전자 수료증이 성취도 페이지에 추가되며, 해당 페이지에서 수료증을 인쇄하거나 LinkedIn 프로필에 수료증을 추가할 수 있습니다. 강좌 콘텐츠만 읽고 살펴보려면 해당 강좌를 무료로 청강할 수 있습니다.

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