Text mining, also known as text analytics or natural language processing, NLP involves extracting meaningful information and insights from unstructured text data.
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Here's a real time example of text mining.
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Social media sentiment analysis.
00:18
Imagine a company that wants to understand public sentiment towards its brand.
00:23
They collect a large volume of customer feedback from social media platforms like Twitter, Facebook and online forums.
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To gain insights from this unstructured text data, they employ text mining techniques, including sentiment analysis.
00:40
Data Collection The company gathers relevant social media posts and comments that mention their brand name or products services.
00:49
Text preprocessing before analysis.
00:52
The text data is preprocessed by removing stop words, common words like, and the, etc.
00:58
Special characters and converting the text to lowercase.
01:03
The data is then tokenized into individual words or phrases.
01:08
Sentiment analysis.
01:10
Using techniques like machine learning or lexicon based approaches, sentiment analysis is performed on each text entry.
01:18
The goal is to determine the sentiment expressed in the text, such as positive, negative or neutral.
01:25
Visualization The sentiment analysis results are visualized using charts or graphs to provide a comprehensive view of public sentiment towards the brand.
01:35
For example, a sentiment analysis dashboard may display the percentage of positive, negative, and neutral sentiments over time or across different customer segments.
01:46
Insights and Action By analyzing the sentiment patterns, the company can identify areas where they are performing well or areas that require improvement.
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They can uncover recurring complaints, identify trends or gauge the impact of specific marketing campaigns.
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This information can guide decision making and help the company respond to customer concerns effectively.
02:11
Through text mining and sentiment analysis, the company can gain valuable insights into customer perceptions, brand reputation and identify opportunities to enhance customer experience and satisfaction.
02:25
This can inform their marketing strategies, product development and customer relationship management efforts.
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