Consumer insights analysis using word embeddings

In one embodiment, a method includes receiving a request to generate k words that each approximates a representation of a relationship between two concepts, where the request includes two input n-grams that each represent one of the two concepts, accessing a table of word vector relationships, where the table includes a plurality of unique n-grams and their corresponding word vectors, looking up word vectors corresponding to each of the two input n-grams using the table, calculating an average vector of the word vectors corresponding to the two input n-grams, selecting, using the table and based on a similarity metric, k word vectors closest to the average vector in the embedding space, identifying, for each of the selected word vectors, a corresponding n-gram by looking up the selected word vector in the table, and sending a response message, the response message comprising the identified n-grams.