We wanted to allow content contributors to provide more context within messages and content consumers to derive greater context while scanning a message stream. Feedback from the community indicated that insight into overall community sentiment on a given symbol or ticker would be valuable.
Users asked us for sentiment around stocks for quite a while. We wanted to add value to the messages being shared and provide context for consumers of the content.
I lead the creative and experience design and was responsible for wireframes, high-fidelity mockups and front-end development for the sentiment tags within the message stream.
We knew sentiment had to be easy to express in a message. Our platform relies on the 140 character limit. Research revealed users didn't like the idea of using a portion of their 140 character limit to express sentiment. We developed a toggle for the StockTwits message box that would allow users to quickly express sentiment in a message without using any of their available message characters. Sentiment would appear in the message itself when published as a "Bullish" or "Bearish" tag.
Initial adoption and usage of the feature was gradual. However, as consumers began to notice the tags in the stream usage increased. Users even began to request that messagers share sentiment when they post.
The increased use of the sentiment feature lead us to create StockTwits Signals. Not only did we enhance the visualization of sentiment on the StockTwits symbol page, we created an entire feature containing various social data visualization to help users see market sentiment trends in real-time.
“just wanted to let you know, I really like the Bear/Bull feature for posting one's bias.“