This project is read-only.

Popular social networks such as LinkedIn, Facebook, and Twitter provide their users with a functionality called a news feed. Such feeds may contain content the users publish, news updates generated by the social networks themselves or third parties, and information on users’ activities. The feeds also contain information about relationships and connectivity updates among the users. An example of a common feed update in Facebook is “Mr. Lemon Grass is now friends with Mrs. Ginger and n other people.” In LinkedIn, a common example of an update is “Mr. Corn is now connected to Mr. Asparagus, Ms. Bamboo Shoots, and Mr. Kohlrabi.” From a user’s perspective, one limitation of such feeds is that they commonly present only recent activity. The user may have the option to look at older content for a limited time that is defined by the social network’s management, such as one month ago to the present. This limitation prevents users from viewing older content. Another limitation of such news feeds is that they do not let the users search for specific events or keywords in the feed.

Here I present LinkedIn Feed Grabber, a proof-of-concept application I developed, dedicated to LinkedIn’s RSS feed (The Network Updates Feed). When a personal LinkedIn Network Updates feed is configured, launching the application parses the feed and places all its events into the user’s Microsoft Outlook Calendar, including the event topic, date of occurrence, description, associated links, etc. Launching the application periodically will continuously update the user’s calendar with new feed events. This is useful for research and allows the user to have feed content stored locally in the Outlook Calendar, providing easy and intuitive access to the feed’s content along with access to the feed’s content for extended periods of time, and allows him/her to search for specific information at any time. Another reason to use the feed grabber application with Microsoft Outlook Calendar is in addition to conducting a regular search (based on specifying a keyword or a set of keywords), to conduct a user-centric activity search, a functionality not available for LinkedIn’s users. This tool can also be used to analyze one’s activity if certain events or actions occur more than others during certain periods and to predict internal and external behavioral and organizational trends. Finally, continuously storing news feeds in a centralized location from multiple social networks (e.g., Ms. Tomato’s activity in Facebook, Twitter, and LinkedIn) will allow one to conduct analysis and research on scenarios that have not yet been sufficiently explored. Such centralized cross-social network data ingestion could be applied in more advanced ways, such as by using cloud platforms, such as Microsoft Azure. This is just a basic implementation (a several-hour project) and can be extended using advanced visualization/charting capabilities, and machine learning techniques.

Enjoy!

Uri Kartoun

Last edited Nov 3, 2012 at 12:04 AM by kartoun, version 16