Knowledge Graph

Think of the Knowledge Graph as a map of an individual’s intellect expressed through social speech. This valuable way of defining the subject matter of social content defines the relationship between terms and entities, with an understanding that certain terms can help identify others.

Example: "Strikers" might be confusing, but if there is a reference to a soccer player in some other way, the system can infer that "Strikers" in that conversation is referencing soccer players.

This tool also contextualizes ambiguous terms to more accurately pinpoint what the writer is referencing.

Example: An individual referencing "apple" may be referring to the fruit. They also may be citing references to the brand. Our Knowledge Graph tool eliminates the confusion.

Twitter icon with message blurb showing social sentiment analysis visual

Sentiment Analysis

Sentiment is expressed differently on social platforms. Social content can be heavily short-form text, produced outside the norms of typical grammar, using devices like emoji and hashtags. Thus, within an artificial intelligence system, the training data must follow suit, along with the analytical methodology.

As a result of this focus, our accuracy is in the high 70% range, as opposed to the mid-50% range you will find with existing sentiment models.

Our Sentiment Analysis currently provides general sentiment of social speech. Future work will allow the tool to judge sentiment based on specific keywords.

outline of person with items popping out of their head representing online personality

Personality

Personality is the greatest predictor of both current preference and future behavior. Our social science team has built our personality profiling model based upon the HEXACO instrument, the most advanced psychological instrument available for personality. This method is also widely applicable and is relevant to every culture and geography.

Our API returns a score for each of the six HEXACO dimensions based on the analysis of social content. Inducing the happiness of an introvert? That would put them in a buying mood. Targeting the naturally curious? They want the product details. The uses are limitless.

Available by the end of November 2017.

Image Object Detection

Given the low semantic payload of messages on some major social networks that focus on communication through other forms, such as images, we understand there is a concrete need to analyze more than the limited descriptions and hashtags that surround those images. We have to glean true understanding and insight from the focal point of the speech, which is the image itself.

Soulmates.ai Image Object Detection has been built to identify and label objects within images that help provide context for social speech via imagery. The objects can help provide insight into people’s interests, preferences, and likelihood of the perceptiveness to particular brands and messaging.

Available by the end of November 2017.

Speech-To-Text

Similar to image recognition, we believe there is a tremendous amount of information being lost by not extracting speech from video. With Speech-to-Text, we extract meaningful information from videos that aids in enrichment and classification for search.

Our solution processes the spoken audio within the video file and saves it as text. We can then run the audio text through many of our other available NLP tools (e.g., Personality, Sentiment Analysis, Knowledge Graph, etc.).

Available by the end of December 2017.

Bot Detection

Whether you run a social data platform or are looking for more information about the influencers you use, understanding whether engagement and resonance is human is now a baseline. Our Bot Detection separates the voices from the machines, and aids in determining the real value of your content and social efforts.

Our bot detection distinguishes channels that are correlated with high value characteristics (influential humans and institutions) and those with low value attributes, like bots. Our model then becomes more precise over time given these traits and categorizations.

Available by the end of November 2017.

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