• Be aware of Filter Bubbles!

    Filter Bubbles (theorized by Eli Pariser) trap the user in protective bubbles created by search engines and platforms, using filters in an automatic and often implicit way.

  • Personalize your social media

    With MIB the user can enhance the dynamism and diversity of content displayed and searched on the Web, removing those constraints that may make it incomplete, unreliable, or even false.

  • Customize your filters...

    MIB provides the active involvement of users, which can customize their search results and views, in accordance with criteria dynamically defined.

  • Evict bots, fake and spammers!

    MIB allows the user to remove malicious information from query results and social media, introducing efficient solutions to distinguish fakers, bot and spammers.

MIB: enhancing the user awareness on Search Engines and Social Media

The increasing use of the Internet and social media for the management of relational networks and for research and information sharing raises significant questions about the information quality. Eli Pariser, a specialist in viral dissemination of relevant content on the Internet, talks about the phenomenon of Filter Bubbles, where users are unknowingly trapped in protective bubbles created by search engines and applications, which adopt filters in an automatic and often implicit way.

The reliability and validity of content shared online are also threatened by another important factor: the phenomenon of fake, e.g., fake content and fake profiles. Bogus reviews, introduced to discredit (or advertise ) products, services, and events, alter users' choices and influence public opinion and, eventually, the market.

The main objective of MIB is to give back to users the control of reachability, authenticity, and relevance of the information available on social media and the Web. The goal will be achieved through the implementation of a mechanism, the ``My Information Bubble", whose implementation will run on the most popular platforms on the web (e.g., Google) and the social media (e.g., Twitter and Facebook):

  • 1) breaking down the filter bubbles (the automatic filtering of the data),
  • 2) identifying false information, and
  • 3) giving the user the possibility to dynamically customize the interaction with social platforms and search engines.

The MIB project started in June 2014 and will last for two years. It is funded by Registro.it and hosted at IIT (Institute of Informatics and Telematics) of the Italian National Research Council (CNR).