Highlights
The Daylight feature where you can quickly view high-level insights about your project. Use Highlights to orient yourself to your project and start navigating the questions you can answer using Daylight.
Volume
Use Daylight’s Sentiment feature to evaluate whether concepts are positive, negative, or neutral based on their context. Using deep learning, Sentiment offers you a highly granular view into how users really feel about your services and offerings.
Sentiment
Use Daylight’s Sentiment feature to evaluate whether concepts are positive, negative, or neutral based on their context. Using deep learning, Sentiment offers you a highly granular view into how users really feel about your services and offerings.
Drivers
Find terms that are prevalent and reveal a significant impact on a measurable aspect of your data in Daylight’s Drivers feature. For example, in a restaurant review project where “scores” are star ratings, the concept “long line” might be a negative driver. A driver’s impact represents the difference between the average score for all documents […]
Galaxy
In the Galaxy feature, view strong conceptual relationships are in the context of your entire project. The size of a concept in the visualization indicates how relevant it is in the project. Related concepts cluster together by theme. You can also use Galaxy to manage concepts.
Document
A document is a single unstructured natural language text sample and optional metadata that you upload to Daylight or classify using Compass. In a CSV file, a document is one row. Most Daylight projects are made up of thousands of documents.
Project
The basic unit of analysis in Luminoso Daylight. A project is built out of a set of unstructured text samples and associated metadata that make up documents. Each project is built based on words in context, so concepts and metrics are unique to each project.
Exact match
An exact match is an identical match to a concept you select. For example, if you analyzed the concept “app,” exact matches might include the concept “app,” “App”, or “apps” but not closely related concepts like “tablet” or “download.”
Association score
Association scores measure how related two concepts are on a scale of -1.00 to 1.00. These numbers represent the weakest and the strongest possible relationships. A concept has an association score of 1.00 with itself. A score of 0 indicates that two concepts are only as associated with one another in a project as they […]
Metadata
Any additional data that accompanies the unstructured text on a document. Metadata could include information like date, number, star rating, or demographic. You can also include qualitative labels like “male,” or “Massachusetts.” After uploading metadata, sort and filter your data to drill down to specific insights