What is Scraawl TxT?What is Scraawl TxT?
An advanced social media and online data analytics tool
TxT is a search and analytics toolbox that leverages advanced machine learning techniques to facilitate knowledge discovery from unstructured text. TxT offers context-aware multi-source text information extraction and extends current search and analysis capabilities by enabling the exploration of large bodies of text. Analysts can quickly search and explore large volumes of unstructured text; identify the most relevant and valuable information; and discover and monitor interesting patterns of topics, opinions, and/or interactions.---
What Can Scraawl TxT Do For You?What Can Scraawl TxT Do For You?
Leverage natural language processing and graph analytics for data exploitation
TxT provides analysts with an interactive dashboard for scalable discovery from scattered, heterogeneous datasets (both structured and unstructured) such as news articles, reports, blogs, documents, comments, chat transcripts, SMS, and e-mail. With TxT users can perform multidimensional search for key actors, discover topics, events, and relationships of interest, topic clusters, and compare analysis results based on context variables such as time, authorships, sentiment, and source. With TxT, users can perform multidimensional search for key actors; discover topics, events, and relationships of interest; and compare analysis results based on context variables such as time, author, sentiment, or source.---
Knowledge Management and Discovery
Use TxT to ingest and index corporate documents across departments, groups, and divisions. Discover knowlege across documents using advanced analytics that go beyond keyword searches. Improve efficiency with quick access to information and fewer redundant efforts.
Brand Monitoring and Customer Support
Use TxT to ingest and integrate information from customer channels such as e-mails, social media posts, chat forums, blogs, and feeds. Intelligently search across channels, discover common topics, identify customer sentiment and similar complaints, and apply the insights gained to improve customer support.
Data Forensics and Fraud Detection
Use TxT to ingest and analyze heterogeneous text data to decrease the time associated with the search and discovery of fraudulent activities. Rapidly correlate information across documents for forensic analysis by finding similar documents, entity names, or entity relations.