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Will the Future of Search
be Semantic in 2021?
www.repustate.com
Table of Contents
● What is news monitoring?
● What is news sentiment analysis?
● How do you scrape news data from the internet using
Python?
● What are the benefits of news monitoring?
● Why choose Repustate’s Text Analytics API for news
monitoring?
Sentiment Analysis for News
Monitoring
Are you looking to manage your brand reputation online? News
monitoring is the process of extracting references to your brand from
mainstream media. News sentiment analysis takes those mentions
and scores them for positive or negative sentiment. This allows you
to understand how the public feels about your company.
These insights can be applied to improve your brand’s competitive
advantage and market share. If you want your company to prosper,
you must look for brand insights in those channels where people are
expressing their feelings toward it. News coverage is one of those
channels.
What is news monitoring?
News is the retelling of recent important events, issues, or influential people. This relevant information can
include business stories that mention companies, brands, and cultural trends. News stories can cover topics like
crime, economics, politics, and entertainment. News can be broadcast through a variety of channels using
various media. Thijs Woltering, Manager of Media Analysis at Media Info Groep in the Netherlands, defines
news monitoring as “the monitoring of at least all editorial news in the entire media landscape.”
In addition to brand mentions, news monitoring can also be applied to extract references to:
● Competing brands and companies
● Geo-political issues that impact the economy
● Important new political policies and legislation
● Mentions of executives and board members
What is news sentiment analysis?
News sentiment analysis takes the basic principles of sentiment
analysis and applies them to brand mentions in the news. Sentiment
analysis pairs machine learning with natural language processing for
text analytics to score high-value information from news coverage and
gauges the opinions expressed as negative, positive, or neutral.
Sentiment analysis can also be applied to videos from news websites
and YouTube through video content analysis. Online reputation
suggests the perspectives consumers have about your brand as
expressed through online channels.
Your brand is ultimately how people perceive your company, whether in a positive or negative light. Various
groups can express their opinion about your company in the news. Various individuals who are influential on
public opinion can speak about your business in the media. People such as:
1. Consumers
2. Company executives
3. Journalists
4. Analysts
5. Influencers
These individuals can all have an immense effect on whether consumers choose to buy from you or do business
with you. This is why applying sentiment analysis to news monitoring is so essential. Here is an example news
sentiment analysis of how a Subway Sandwiches online brand reputation was recently affected by Irish legislation
How do you scrape news data from the
internet using Python?
Many companies employ web scraping for news monitoring. Web scraping is a technique used to browse the
internet to search for a piece of particular information. A web scraping tool makes copies of the entire content
of a website, copies its data, and then runs a code through it to parse the data and extract the parts you
want. Some websites allow web scraping, while others are less inviting, as web scraping can lead to an
unprecedented spike in web traffic resulting in a website crash.
Python is used for web scraping not only because it is easy to use, but also because it is perfect for collating
information from a huge amount of data. The most widely used modules in the Python library for web
scraping are Selenium, Beautiful Soup, and Requests. They can be used individually, as well as together.
Selenium can automate different events like clicking and scrolling on the targeted website and is mostly used
for website testing. It is especially helpful if you need to interact with JavaScript.
Why choose Repustate’s Text Analytics
API for news monitoring?
Which Are The Most Important Sources
Of Collecting Customer Insights?
Thank you!
Understand your data,
customers, & employees with
12X the speed and accuracy.
Visit: www.repustate.com to
learn more

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News sentiment analysis

  • 1. Will the Future of Search be Semantic in 2021? www.repustate.com
  • 2. Table of Contents ● What is news monitoring? ● What is news sentiment analysis? ● How do you scrape news data from the internet using Python? ● What are the benefits of news monitoring? ● Why choose Repustate’s Text Analytics API for news monitoring?
  • 3. Sentiment Analysis for News Monitoring
  • 4. Are you looking to manage your brand reputation online? News monitoring is the process of extracting references to your brand from mainstream media. News sentiment analysis takes those mentions and scores them for positive or negative sentiment. This allows you to understand how the public feels about your company. These insights can be applied to improve your brand’s competitive advantage and market share. If you want your company to prosper, you must look for brand insights in those channels where people are expressing their feelings toward it. News coverage is one of those channels.
  • 5. What is news monitoring? News is the retelling of recent important events, issues, or influential people. This relevant information can include business stories that mention companies, brands, and cultural trends. News stories can cover topics like crime, economics, politics, and entertainment. News can be broadcast through a variety of channels using various media. Thijs Woltering, Manager of Media Analysis at Media Info Groep in the Netherlands, defines news monitoring as “the monitoring of at least all editorial news in the entire media landscape.” In addition to brand mentions, news monitoring can also be applied to extract references to: ● Competing brands and companies ● Geo-political issues that impact the economy ● Important new political policies and legislation ● Mentions of executives and board members
  • 6. What is news sentiment analysis? News sentiment analysis takes the basic principles of sentiment analysis and applies them to brand mentions in the news. Sentiment analysis pairs machine learning with natural language processing for text analytics to score high-value information from news coverage and gauges the opinions expressed as negative, positive, or neutral. Sentiment analysis can also be applied to videos from news websites and YouTube through video content analysis. Online reputation suggests the perspectives consumers have about your brand as expressed through online channels.
  • 7. Your brand is ultimately how people perceive your company, whether in a positive or negative light. Various groups can express their opinion about your company in the news. Various individuals who are influential on public opinion can speak about your business in the media. People such as: 1. Consumers 2. Company executives 3. Journalists 4. Analysts 5. Influencers These individuals can all have an immense effect on whether consumers choose to buy from you or do business with you. This is why applying sentiment analysis to news monitoring is so essential. Here is an example news sentiment analysis of how a Subway Sandwiches online brand reputation was recently affected by Irish legislation
  • 8. How do you scrape news data from the internet using Python? Many companies employ web scraping for news monitoring. Web scraping is a technique used to browse the internet to search for a piece of particular information. A web scraping tool makes copies of the entire content of a website, copies its data, and then runs a code through it to parse the data and extract the parts you want. Some websites allow web scraping, while others are less inviting, as web scraping can lead to an unprecedented spike in web traffic resulting in a website crash. Python is used for web scraping not only because it is easy to use, but also because it is perfect for collating information from a huge amount of data. The most widely used modules in the Python library for web scraping are Selenium, Beautiful Soup, and Requests. They can be used individually, as well as together. Selenium can automate different events like clicking and scrolling on the targeted website and is mostly used for website testing. It is especially helpful if you need to interact with JavaScript.
  • 9. Why choose Repustate’s Text Analytics API for news monitoring?
  • 10. Which Are The Most Important Sources Of Collecting Customer Insights?
  • 11. Thank you! Understand your data, customers, & employees with 12X the speed and accuracy. Visit: www.repustate.com to learn more