Breaking Barriers in Research with Kimola's New NLP Datasets

Dec 12, 2023 - 3 min read
Breaking Barriers in Research with Kimola's New NLP Datasets

We are thrilled to share that our comprehensive NLP Datasets repositor is now available on Kimola's GitHub: Kimola NLP Datasets. This initiative underscores our commitment to fostering research excellence by providing valuable resources to the global community of data enthusiasts, analysts, and researchers.

Kimola Cognitive - Github

About Our Mission

From Ice Cream Shops to Beauty Salons; Research is for everyone.

Dive into 20+ datasets covering a spectrum of businesses, from the enchanting Giolitti (Ice Cream Shop in Rome) to the sophisticated Carita (Beauty Salon in Paris), the fitness haven AbsoluteYou (Fitness Center in Singapore), and even the iconic Borsalino (Hat Boutique in Milan). We believe that by offering diverse datasets, we empower researchers to explore and uncover insights in a multitude of business areas.

Additionally, we encourage researchers leveraging our free datasets to champion our cause. Spread the word about Kimola Cognitive, where small and medium-sized businesses can conduct analyze customer feedback and conduct research to scale their ventures, whether it's an ice-cream shop, a beauty salon, or a hat shop on a quaint street corner. Let us collectively advocate for the democratization of research, asserting that research is everyone's right, not just a privilege for established enterprises.

Together, we can amplify the impact of accessible research and empower businesses of all sizes to thrive.

A Treasure Trove of Customer Feedback from Diverse Sources

Our NLP Datasets compilation is a goldmine of customer feedback collected from an array of platforms, including Trustpilot, Amazon, TripAdvisor, Google Reviews, App Store, G2 Reviews, and more. These datasets are collected with Kimola Cognitive’s Airset Generator, a browser extension that can scrape data from various sources for free. Each dataset is meticulously curated to ensure relevance and diversity, offering a rich tapestry of consumer insights spanning various industries, products, and services.

Structured for Seamless Analysis

Understanding the unique challenges posed by different consumer behaviors, we've structured the datasets by product/company name, business type, and the channel from which the reviews were scraped. This meticulous organization allows researchers to extract meaningful patterns and conduct in-depth analyses tailored to their specific areas of interest while using Kimola Cognitive, or any other text analysis tool.

Multi-Lang Capabilities for Global Insights

Recognizing the global nature of online platforms, our datasets naturally feature reviews in different languages. We've taken care to clean the data, considering review length, to facilitate a more nuanced and accurate analysis, ensuring that researchers can extract valuable insights regardless of language barriers.

Access and Utilization

Kimola is dedicated to democratizing research. Researchers and marketing professionals can utilize these datasets in two ways:

Local Analysis: Download datasets of interest and leverage them for local analysis, research, or training NLP models. The CSV format ensures compatibility with various data analysis tools and programming languages.

Kimola Cognitive: For a more advanced and seamless analysis experience, leverage Kimola Cognitive. Simply drag and drop your dataset files onto our platform to access actionable insights through advanced AI analytics. Sign up for a 7-day free trial on our website to unlock the full potential of customer feedback analysis.

 

Community Contributions

Our commitment doesn’t stop here. We will regularly update the repository with new datasets to cater to the evolving needs of marketing and research professionals. If you create new datasets or improve existing ones using Airset Generator, we encourage you to share them with us. Our community, fondly referred to as dataholics, is integral to our mission of enabling research for everyone.

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