Editor’s note: Minerva Singh will be speaking on the Ai+ Training platform on December 14th. Be sure to check out the session, “Web Scraping & Social Media Mining for Text Analysis & NLP” for 10% off now.
Text analytics, social media mining, and web scraping are becoming paramount to a company’s success. As text data is so prevalent on social media, a business can use readily-available information to make informed decisions quickly, consistently, and effectively. We recently had the chance to speak with Minerva Singh, PhD, a deep learning instructor, on social media analytics and some of the tools she uses daily.
What got you into webscraping and social media mining?
What are some interesting use-cases that you’ve been a part of or have seen in regards to webscraping?
Some of the professional advantages an organization can get from web scraping include: (a) Price Monitoring: You can scrape product prices from a variety of sources including Amazon and use that for pricing decisions (b) Social Media Insights: Dive into social media chatter and identify upcoming trends (example, GME mania) (c) Potential Lead Generation: Web scraping can also help you personally (and professionally) by supporting data-driven decision-making. For instance, web scraping is a powerful way of assessing real-estate trends in terms of prices and changes. Additionally, you can use webscraping to inform financial decision-making and derive geolocational insights.
Why should a new data scientist learn about webscraping? Do you think it’s an attractive skill set to hiring managers?
Learning webscraping can equip data scientists to take more dynamic roles especially in the fields of marketing, financial services, IT as shown by LinkedIn:
For webscraping and social media mining, I use Python. For the former BeautifulSoup is my go-to.
Anything else you’d like to share?
A practical Python webscraping example: https://www.youtube.
More on Minerva’s session, “Web Scraping & Social Media Mining for Text Analysis & NLP“: This course provides a foundation to carry out PRACTICAL, real-life social media mining. By taking this course, you are taking an important step forward in your data science journey to become an expert in harnessing the power of social media for deriving insights and identifying trends. This course will help you gain fluency both in the different aspects of text analysis and NLP working through a real-life example of cryptocurrency tweets, Wall Street Bet Reddit posts, restaurant reviews, and financial news using a powerful clouded based python environment called GoogleColab.
About Minerva Singh, PhD
I joined the Center for Environmental Policy (CEP), Imperial College London as a Research Fellow in 2018. Before that, I completed a PhD from the University of Cambridge in 2017 where I focussed on implementing data science techniques for quantifying the impact of forest loss on tropical ecosystems. I hold an MPhil (School of Geography and Environment) and an MSc (Department of Engineering) from Oxford University. I have nearly 10 years’ experience in conducting academic research at the interface of tropical ecology, data science, earth observation (EO), and artificial intelligence (AI) and published 14 first-author peer-reviewed papers in international journals since 2013 including PLoS One. I am also a best selling course-instructor on the online MOOC platform Udemy where I provide online teaching to more than 71,000 students from across the world on machine learning, earth observation, and deep learning-related topics.