The Secret Lives of Names? Name Embeddings from Social Media
Table 3. Ratios of same-ethnicity names among nearest neighbors. Aggregated* achieves highest ratios among all Twitter embeddings and gets comparable performance comparing to Email. Follower outperforms Followee, while Followee* has the same average ratio as Follower, which validates that removing celebrities is effective. (API: Asian and Pacific Islander)
['Embedding', 'White', 'Black', 'API', 'Hisp.', 'Avg.']
It is interesting to see Mention gets higher scores than Retweet, indicating more ethnic homophily in mentions. One possible explanation is users are more likely to mention or raise attention from their friends while retweeting or quoting from the famous ones. So Followee has lower same-ethnicity ratios than Followers. After removing celebrity names, Followee* outperforms similarly as Follower. The superior performances of Followee* over Followee on both gender and ethnicities validate less homophily among celebrity-fan pairs and the effectiveness of removing celebrities. Therefore, Aggregate* performs best among all Twitter embeddings, after combining training examples from Followee* instead of Followee. Email gets highest ratio among all. Black names are harder to classify because they only take up 3.5% of all labels.