The study explores how language usage and context on a site like Kickstarter can influence whether or not a project gets funded. The researchers used Beautiful Soup, a widely used scraper, to pull down all the text. Afterwards, they tokenized the words into unigrams, bigrams, and trigrams and then trimmed it down even more by removing certain phrases and words so that their model wouldn’t account for the scarce outliers. Outliers in this context were words or phrases that may be only relevant in certain subjects such as “game credits” or “our menu”. The words were then categorized into six categories: reciprocity, scarcity, social proof, and social identity, linking, and authority. Apart from their findings, such as explicitly labeling certain phrases with projects that get funded vs phrases with projects that don’t, one of their suggestion is to perhaps create a FAQ or “Help Center” which can be of aid to the project developers as it’ll help them select words associated with successful pitches.
I’d be interested to see in more detail, an analysis of language usage within successful funded projects vs unsuccessful funded projects. Just because a project was funded does not mean that it was successful. This kind of study would be more to the benefit for the people that fund projects but its long term effects would be that it could help these folks perhaps use their money wisely when deciding to fund a project. Additionally, the methodology and approach used here can help my group’s project as we’re trying to identify which words or phrases are more frequently used in fake news, as oppose to reliable sources.
Do we find the same results of successful/unsuccessful phrases if this was done in a different language e.g. Spanish?
Does a high usage of good or bad phrases have the opposite effect?
