課程信息
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Learner Outcomes: After taking this course, you will be able to: - Utilize various Application Programming Interface (API) services to collect data from different social media sources such as YouTube, Twitter, and Flickr. - Process the collected data - primarily structured - using methods involving correlation, regression, and classification to derive insights about the sources and people who generated that data. - Analyze unstructured data - primarily textual comments - for sentiments expressed in them. - Use different tools for collecting, analyzing, and exploring social media data for research and development purposes. Sample Learner Story: Data analyst wanting to leverage social media data. Isabella is a Data Analyst working as a consultant for a multinational corporation. She has experience working with Web analysis tools as well as marketing data. She wants to now expand into social media arena, trying to leverage the vast amounts of data available through various social media channels. Specifically, she wants to see how their clients, partners, and competitors view their products/services and talk about them. She hopes to build a new workflow of data analytics that incorporates traditional data processing using Web and marketing tools, as well as newer methods of using social media data. Sample Job Roles requiring these skills: - Social Media Analyst - Web Analyst - Data Analyst - Marketing and Public Relations Final Project Deliverable/ Artifact: The course will have a series of small assignments or mini-projects that involve data collection, analysis, and presentation involving various social media sources using the techniques learned in the class....
Globe

100% 在線課程

立即開始,按照自己的計劃學習。
Calendar

可靈活調整截止日期

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Intermediate Level

中級

Clock

Approx. 15 hours to complete

建議:4 weeks of study, 3-6 hours/week...
Comment Dots

English

字幕:English...

您將獲得的技能

Python ProgrammingStatistical AnalysisSentiment AnalysisR Programming
Globe

100% 在線課程

立即開始,按照自己的計劃學習。
Calendar

可靈活調整截止日期

根據您的日程表重置截止日期。
Intermediate Level

中級

Clock

Approx. 15 hours to complete

建議:4 weeks of study, 3-6 hours/week...
Comment Dots

English

字幕:English...

教學大綱 - 您將從這門課程中學到什麼

Week
1
Clock
完成時間為 3 小時

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....
Reading
4 個視頻(共 33 分鐘), 4 個閱讀材料, 2 個測驗
Video4 個視頻
Video-2: Structured vs. Unstructured Data10分鐘
Video-3: Analyzing Structured Data10分鐘
Video-4: Visualization of Data8分鐘
Reading4 個閱讀材料
Anaconda Installation20分鐘
Python installation, configuration, and usage30分鐘
R installation30分鐘
R/RStudio Setup Guide (on Windows)20分鐘
Quiz2 個練習
Quiz-115分鐘
Quiz-215分鐘
Week
2
Clock
完成時間為 4 小時

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....
Reading
4 個視頻(共 47 分鐘), 6 個閱讀材料, 3 個測驗
Video4 個視頻
Video-2: Introduction to Python Programming16分鐘
Video-3: Using Python to Extract Data from Twitter15分鐘
Video-4: Using Python to Extract Data from YouTube11分鐘
Reading6 個閱讀材料
Errata: please read this first1分鐘
Python Packages Installation5分鐘
(Optional) Introduction to Python for Econometrics, Statistics and Data Analysis30分鐘
Script: twitter_search.py分鐘
Twitter libraries10分鐘
Script: youtube_search.py分鐘
Quiz2 個練習
Python Programming Exercise2分鐘
YouTube data download using Python6分鐘
Week
3
Clock
完成時間為 4 小時

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....
Reading
4 個視頻(共 87 分鐘), 8 個閱讀材料, 2 個測驗
Video4 個視頻
Video-2: Analyzing Social Media Data Using Python26分鐘
Video-3: Introduction to R26分鐘
Video-4: Social Media Data Analysis with R32分鐘
Reading8 個閱讀材料
Script: twitter_process.py分鐘
Data: iqsize.csv分鐘
R Installation Guide10分鐘
Installing R Packages5分鐘
Statistical Analysis with R10分鐘
Read this first2分鐘
Scripts for converting json to csv2分鐘
Data Visualization with ggplot2 (R) - Cheat Sheet10分鐘
Quiz1 個練習
Statistical Analysis with Twitter Data6分鐘
Week
4
Clock
完成時間為 3 小時

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....
Reading
4 個視頻(共 47 分鐘), 4 個閱讀材料, 2 個測驗
Video4 個視頻
Video-2: Sentiment Analysis with Twitter Data21分鐘
Video-3: Text Mining of Twitter Data15分鐘
Video-4: Conclusion6分鐘
Reading4 個閱讀材料
Script: twitter_sentiments.py分鐘
NLTK10分鐘
Script: text_mining_twitter.r分鐘
An Introduction to Network Analysis with R and statnet10分鐘
Quiz1 個練習
Sentiment Analysis with Twitter6分鐘

講師

Chirag Shah

Associate Professor
Information and Computer Science

關於 Rutgers the State University of New Jersey

常見問題

  • Once you enroll for a Certificate, you’ll have access to all videos, quizzes, and programming assignments (if applicable). Peer review assignments can only be submitted and reviewed once your session has begun. If you choose to explore the course without purchasing, you may not be able to access certain assignments.

  • When you purchase a Certificate you get access to all course materials, including graded assignments. Upon completing the course, your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.

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