The extraordinary productivity of foul language – Do you and your text analytics solution know these bad words?
By looking into the extraordinary productivity of foul language, this post showcases the ability of the Gavagai’s semantic memories to automatically learn and relate terms in a vocabulary. If you are sensitive to swearing and cursing, you should stop reading now! Foul language, profanity, expletives, and bad words. The creativity of the human mind when it comes to inventing impolite, rude or offensive language is simply amazing. But regardless of how productive a single human being might be, she still will never be able to come up with all the variants of a given bad language concept used throughout an…
What is an efficient way to analyze answers to open-ended survey questions using language technology?
There are challenges to analyzing free-text answers. In the following discussion I will assume that the purpose of the analysis is to achieve an understanding of the themes being discussed and the relative strengths of these themes as well as to get accurate quantification of the numbers of respondents and percentages for each theme. Knowing about multiword expressions. Important concepts in text often consist of more than one word, for example: “San Francisco”, “no-fly zone”, “give me five”, or “kick the bucket”. An automated tool for analysis of answers to open-ended survey questions needs to understand such multiword expressions or the…
Poor Panama – The Central American state’s name is heavily associated with the events at Mossack Fonseca
Poor Panama. Since the investigation around the Panama Papers was made public earlier this month, mentions of the Republic of Panama in online media has been heavily associated with negative connotations such as “tax evasions”, and “shell companies”, and “leaked documents”. Although more intended as a way of inspecting the state of the semantic memories, the Gavagai Living Lexicon can also serve as a probe into the state-of-mind of the online media. As illustrated in the screenshot of the Lexicon below, “Panama” has, as of this writing, an unfortunate relation to “Mossack Fonseca” (click the image for a larger version). How will…
Making sense of 14793 answers to the question: “What do you most wish for the coming year?”
In order to better understand their customers’ thoughts and wishes for the coming year, AMF – a limited liability life insurance company that is owned equally by the Swedish Trade Union Confederation (LO) and the Confederation of Swedish Enterprise (Svenskt Näringsliv) – sent out a survey to more than 100 000 senior citizens. The survey included the open-ended question: What do you most wish for the coming year? Read the case study on how Gavagai Explorer was used to make sense of the 14793 answers to that question here.
Understanding the Whats and Whys of a Net Promoter study at scale
What concerns Detractors? What make Promoters promoters? In this case study, we use Gavagai Explorer to acquire insight into the answers of an open-ended follow-up question in a Net Promoter Score survey of the Swedish Telecom business with 2535 respondents. Net Promoter Score (NPS) is a metric for measuring the loyalty of a company’s customers based on their feedback. NPS is widely used across all kinds of industries, for instance in the travel and hotel business, software services, and telecommunications. Typically, NPS surveys are conducted continuously, so as to assess the performance of an organization over time. Each survey may…