August 9, 2016
Emojis are a secondary language for many people, especially the younger sect, and whole messages can be conveyed within a few images. Someone needs to write an algorithm to translate emoji only messages, but machine learning has not yet reached the point where it can understand all the intricacies associated with emojis. Or has it? TechCrunch shares that “Dango Mind-Melds With Emoji Using Deeping Learning And Suggests Them While They Type.”
Dango is an emoji suggestion chatbot. Unlike the Microsoft chatbot that became anti-Semitic and misogynist in a matter of hour, Dango just wants to give you emoji suggestions to pep up your messages:
“Okay, so Dango is one of those virtual assistants that lives in your chat apps, and this one is based on a neural network that has been trained with millions of examples to understand what emoji mean. So not only can it suggest an appropriate one, but it can translate entire sentences. Its icon is a weird piece of cute cake, which sits above your keyboard watching you type. It’s free for Android right now, with an iOS version coming out eventually.”
Aww, it’s a little cake icon that sits above your keyboard. Is it not tempting already to download it make Dango your friend? The cute factor comes after the deep machine learning took place.
The Dango programmers used a recurrent neural network to teach Dango how to decipher the meaning of emoji. It would guess, then check against real world examples, then adjust its parameters when it was wrong. The guesses were assembled in a “semantic space” that relates the emojis to concepts (check the article for the visualization).
Dango is constantly updating itself to be on top of the latest slang and memes, including the negative aspects of the language. Dango is still learning, especially when it comes to translating entire sentences to pictures. Before you say that the written language cannot be replicated in little images, it was done eons ago by Egyptians, Sumerians, Phoenicians, and still by the Chinese, Japanese, and other Asian cultures.
There is a Louisville, Kentucky Hidden /Dark Web meet up on August 23, 2016.
Information is at this link: https://www.meetup.com/Louisville-Hidden-Dark-Web-Meetup/events/233019199/
June 1, 2016
It was only a matter of time after image search actually became a viable and useful tool that someone would develop a GIF search. Someone thought it would be a keen idea to also design an emoji search and now, ladies and gentlemen, we have it! Tech Viral reports that “Now You Can Search Images On Google Using Emoji.”
Using the Google search engine is a very easy process, type in a few keywords or a question, click search, and then delve into the search results. The Internet, though, is a place where people develop content and apps just for “the heck of it”. Google decided to design an emoji search option, probably for that very reason. Users can type in an emoji, instead of words to conduct an Internet search.
The new emoji search is based on the same recognition skills as the Google image search, but the biggest question is how many emojis will Google support with the new function?
“Google has taken searching algorithm to the next level, as it is now allowing users to search using any emoji icon. Google stated ‘An emoji is worth a thousand words’. This feature may be highly appreciated by lazy Google users, as they now they don’t need to type a complete line instead you just need to use an emoji for searching images.”
It really sounds like a search for lazy people and do not be surprised to get a variety of results that do not have any relation to the emoji or your intended information need. An emoji might be worth a thousand words, but that is a lot of words with various interpretations.
May 12, 2015
Emojis, different from their cousin emoticons, are a standard in Internet jargon and are still resisted by most who grew up in a world sans instant connection. Mike Isaac, who writes the New York Times Bits blog, tried his best to resist the urge to use a colon and parentheses to express his mood. Isaac’s post “The Rise Of Emoji On Instagram Is Causing Language Repercussions” discusses the rise of the emoji language.
Emojis are quickly replacing English abbreviations, such as LOL and TTYL. People are finding it easier to select a smiley face picture over having to type text. Isaac points to how social media platforms like Facebook, Twitter, Instagram, and Snapchat users are relying more on these pictograms for communication. Instagram’s Thomas Dimson mentioned we are watching the rise of a new language.
People string emojis together to form complete sentences and sentiments. Snapchat and Instagram rely on pictures as their main content, which in turn serves as communication.
“Instagram itself is a means of expression that does not require the use of words. The app’s meteoric rise has largely been attributed to the power of images, the ease that comes, for instance, in looking at a photo of a sunset rather than reading a description of one. Other companies, like Snapchat, have also risen to fame and popularity through the expressive power of images.”
Facebook and Twitter are pushing more images and videos on their own platforms. It is a rudimentary form of communication, but it harkens back to the days of cave paintings. People are drawn to images, because they are easy to interpret from their basic meaning and they do not have a language barrier. A picture of a dog is still the same in Spanish or English. The only problem from using emojis is actually understanding the meaning behind them. A smiley face is easy to interpret, but a dolphin, baseball glove, and maple leaf might need some words for clarification.
Isaac finishes that one of the reasons he resisted emojis so much was that it made him feel childish, so he reserved them for his close friends and family. The term “childish” is subjective, just like the meaning of emojis, so as they become more widely adopted it will become more accepted.
Whitney Grace, May 12, 2015
April 27, 2015
The article on PCWorld titled For Attensity’s BI Parsing Tool, Emoticons Are No Problem explains the recent attempts at fine-tuning the monitoring and relaying the conversations about a particular organization or enterprise. The amount of data that must be waded through is massive, and littered with non-traditional grammar, language and symbols. Luminoso is one company interested in aiding companies with their Compass tool, in addition to Attensity. The article says,
“Attensity’s Semantic Annotation natural-language processing tool… Rather than relying on traditional keyword-based approaches to assessing sentiment and deriving meaning… takes a more flexible natural-language approach. By combining and analyzing the linguistic structure of words and the relationship between a sentence’s subject, action and object, it’s designed to decipher and surface the sentiment and themes underlying many kinds of common language—even when there are variations in grammatical or linguistic expression, emoticons, synonyms and polysemies.”
The article does not explain how exactly Attensity’s product works, only that it can somehow “understand” emoticons. This seems like an odd term though, and most likely actually refers to a process of looking it up from a list rather than actually being able to “read” it. At any rate, Attensity promises that their tool will save in hundreds of human work hours.
Chelsea Kerwin, April 27, 2014
March 13, 2015
Part of big data is being able to make sense of unstructured data, including the pieces that natural language processing software cannot understand like emoticons. Emoticons are an Internet phenomenal where people use grammatical symbols, numbers, and letters to represent feelings and ideas.
They cannot be spoken, so if an organization wants to analysis all of its data they need to be able to interpret emoticons. PC World tells us that Attensity has already created a way to understand emoticons without turning to a teenage girl to translate: “For Attensity’s BI Parsing Tool, Emoticons Are No Problem.”
Attensity’s Semantic Annotation natural-language processing tool was designed to handle large data loads. It can monitor and extract insights from unstructured data, including data from social media platforms and internal information like customer surveys and calls.
“Rather than relying on traditional keyword-based approaches to assessing sentiment and deriving meaning, Attensity’s Java-based product takes a more flexible natural-language approach. By combining and analyzing the linguistic structure of words and the relationship between a sentence’s subject, action and object, it’s designed to decipher and surface the sentiment and themes underlying many kinds of common language—even when there are variations in grammatical or linguistic expression, emoticons, synonyms and polysemies.”
This means Attensity can generate data straight from sentences rendered entirely in emoticons and acronyms.
Another practical use for Attensity’s Semantic Annotation would be to create a translation app for parents trying to decipher their teenager’s text messages.