Hong Kong Productivity Council Academy

Social Media Analytics and Sentiment Analysis in Digital Marketing

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Course Information

Schedules
  • 14 Sep 2021 (Tue) - 16 Sep 2021 (Thu) 9:30 AM - 12:30 PM
Registration period
20 May 2021 (Thu) - 13 Sep 2021 (Mon)
Price
HKD 6,000
(HK$6,000*
Member of HKRMA: 10% off –HK$5,400*

* This course is an approved Reindustrialisation and Technology Training Programme (RTTP ), which offers up to 2/3 course fee reimbursement upon successful applications. For details: https://rttp.vtc.edu.hk)
Course Level
Study Mode
Duration
6 Hour(s)
Language
Cantonese
Location
-
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Course Overview

This programme aims at enabling retail industry practitioners to apply Social Media Analytics and Sentiment Analysis in the industry, which include digital marketing, social listening and customer satisfaction.

In addition, participants will learn how to apply Data Analytics, NLP (Natural Language Processing) and Deep Learning techniques on textual data processing and understanding.

Target Audiences

  • Retail industry practitioners who are interested in applying Social Media Analytics and Sentiments Analysis
  • Professionals who would like to sharpen their skills with the latest AI and Machine Learning technologies
  • SME/start-up entrepreneurs who wish to get inspiration to incorporate social media and sentiments into their businesses

What You’ll Learn

Day 1 (3 hours): Data Collection, Visualisation and Algorithms

  • Social Media data collection, pre-processing and visualisation
  • Massive dataset organisation such as indexing, keywords searching and ranking for relevance
  • Special handling for Chinese and Cantonese languages
  • Case Analysis: Social listening for company/product brandings, KOL and micro influencer identification, Machine Learning algorithm for product cross selling and recommendation

Day 2 (3 hours): Natural Language Processing and Sentiment Analysis

  • Building blocks of Natural Language Processing
  • Word2Vec embedding to understand language semantics
  • Introduction to Deep Learning based techniques for Sentiment Analysis
  • Case analysis: Apply rule-based sentiment APIs to extract customers’ emotions, develop a sentiment analyser by Deep Learning Sequence model (LSTM) to understand customer reviews and sentiments


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