Professional network LinkedIn further integrated itself with Twitter with its limited beta launch Wednesday of LinkedIn Signal, which is aimed at filtering the noise out of users’ streams of status updates, Tweets, and news and enabling them to focus on the most relevant content.
LinkedIn Signal allows users to filter their streams of information from LinkedIn and Twitter based on network, industry, company, time published, geographic region, school, or most popular hash tags, as well as to search by keyword, topic, or person. It creates a real-time stream, alerting users when fresh content is available, and highlights the most popular links, along with who they were shared by.
Its user interface is made up of three main panes, with filter options displayed on the left side, the stream in the middle, and the right side occupied by trending links.
Principal product manager Esteban Kozak wrote on the LinkedIn Blog:
Signal is the first of many LinkedIn products aimed at making it really easy for all professionals to glean only the most relevant insights from the never-ending stream of status updates and news. In other words, Signal allows all professionals to make sense of the noise that surrounds them today.
Hidden in the stream of status updates is information that’s valuable and helps you be better at your job. Signal allows you to hone in on information you’re most interested in, for e.g. updates from your colleagues (even from folks on your same team) or audiences you’re most interested in researching and understanding.
LinkedIn Signal allows you to also search for specific keywords or topics you’d like to keep up to date on. You could also search for your favorite public personalities or a colleague whose updates you’d like to find quickly.
Signal also lets you create very personalized views of the LinkedIn stream that you can check into every day. You can go back to it quickly by simply accessing all your followed searches on the top left rail.
Starting today, we’re going to be rolling out Signal to different groups of our members. We’ll be collecting feedback and analyzing usage patterns for the next few months, while we roll out the feature to the rest of our users. Stay tuned for more.