![]() ![]() In skip-gram mode, word2vec reads through text and predicts the context around a given word or emoji. ![]() We learn the floating point numbers using the Gensim library, which re-implements a tool called word2vec. In the scatter chart below, we embedded words, emoji, and hashtags into a 100-dimensional space of floating point numbers using 50 million English Instagram comments and captions from 2015. The representation of the words are chosen so that similar words have a small distance. More formally, we can place (or embed) emoji and hashtags together with words into a common metric space where there are well-defined distances between elements. It can be applied to emoji by treating them as if they are normal words. For example, we might say that “dog” and “cat” are similar words because they can both be used in sentences like “The pet store sells _ food.” In the field of natural language processing, this intuition is called the distributional hypothesis □. Intuitively, substitutable words have similar meanings. We’re often asked about the meaning of emoji such as □. If the overall trend continues, we might be looking at a future where the majority of text on Instagramcontains emoji. The graph below shows that users from Finland are using emoji characters in over 60% of text! In contrast, the lower bound is in Tanzania with only 10% of text containing emoji. In the future, will all text contain emoji? To help answer that question, we divided emoji usage by country and observed the differences between user cohorts. Usage continued to grow and in March of this year, nearly half of text contained emoji □. Afterwards, there was a clear upward trend which accelerated after Android received native support for emoji in July 2013. The trend continued until the release of Instagram for Android in April of 2012, when many new users did not have emoji support. In the month following the introduction of the iOS emoji keyboard, 10% of text on Instagram contained emoji. The graph below shows the percentage of text (comments and captions) containing emoji characters graphed over time □. Instagram has always supported emoji, but they did not see wide adoption until the introduction of the emoji keyboard on iOS (October 2011) and on most Android platforms (July 2013). It is a rare privilege to observe the rise of a new language. By applying machine learning and natural language processing techniques, we’ll discover the hidden semantics of emoji. In Part 1 of this blog post series, we will take a deep dive into emoji usage on Instagram. And earlier this week, Instagram also added support for emoji characters in hashtags, which allows people to tag and search content with their favorite emoji #□. Since then, digital language has evolved such that nearly half of comments and captions on Instagram contain emoji characters. □□In October 2011, Apple added the emoji keyboard to iOS as an international keyboard. ![]() Emojineering Part 1: Machine Learning for Emoji Trends ![]()
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