Our privacy practices comply with data protection laws, including the EU data protection regulatory framework, GDPR, and the California Consumer Privacy Act of 2018 (CCPA) – respecting requests to exercise privacy rights and more.
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Gain a competitive edge using high-quality, reliable datasets tailored for brands, researchers, and marketing teams.
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Brand & Product Teams
Understand how the world feels about your brand
Researchers & Analysts
Turn public opinion into actionable insight
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Sentiment analysis popular use cases
Product & Brand Sentiment
Financial Market Sentiment
Political & Public Opinion
Customer Support Sentiment
Social Media Sentiment Tracking
Crisis & Reputation Monitoring
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Frequently Asked Questions
Is scraping publicly available data for sentiment analysis allowed?
Yes. Accessing publicly available information via automated means is considered permissible under applicable regulatory and legal frameworks. Bright Data's services emulate the behavior of an individual end user — there is nothing done through our services that cannot be done manually by a human with a web browser. This makes it a legitimate and widely adopted practice for collecting public sentiment data at scale.
Read more: Code of Ethics and Conduct
How does Bright Data ensure compliance when collecting sentiment data?
Bright Data collects only publicly available data — information that does not require a login or sign-in to access. We have made considerable efforts to ensure our privacy practices comply with data protection laws including GDPR and CCPA, and we continuously monitor legal developments to help customers use our services compliantly.
Bright Data has designed a detailed Privacy Policy to provide all required information about its privacy practices.
What sources can be used to collect sentiment data?
Sentiment data can be collected from a wide range of public sources including social media platforms (Instagram, TikTok, Reddit, X), review sites (Amazon, G2, Trustpilot), news outlets, forums, and community boards. Bright Data's infrastructure supports scraping across all of these source types at scale.
Does Bright Data collect personal data during sentiment data collection?
Bright Data collects publicly available data only — information that does not require a login or sign-in to access. While some public content may incidentally include personal data (such as a username or public profile), personal data collection is not our objective, and we operate strictly within applicable legal frameworks.
What security measures does Bright Data have in place to protect customer data?
Bright Data manages data for over 15,000 organizations around the world. Our security model and controls are based on international standards and industry best practices, including ISO 27001, ISO 27018, CSA Star level I, and OWASP Top 10, as well as best practices for data encryption, infrastructure security, and external security audits.
How often is sentiment data updated?
Datasets are refreshed upon request prior to purchase to ensure the most current information. For ongoing sentiment monitoring use cases, update frequency can be customized — from near real-time to daily or weekly — depending on your specific needs.
Do you include images or media in sentiment datasets?
Records include URLs to images and media where available. In some cases, images can be acquired as separate datasets. This is particularly relevant for visual sentiment signals from platforms like Instagram and TikTok.
Can I get a larger sample to test the sentiment data with my system?
Yes, we can provide larger samples; please contact our sales representatives.
Can you combine sentiment data from multiple sources?
Yes. We can perform queries combining datasets from multiple sources — for example, merging review data from Amazon with social media signals from Reddit — assuming a common identifier exists. Please contact our data experts if you have such a need.
Do you have historical sentiment data available?
Yes. When we refresh a dataset, we store some or all of its past values. We have up to 1 year of historical sentiment data for most datasets, enabling trend analysis and longitudinal sentiment tracking.