Twitter has become a major tool for spreading news, for dissemination of positions and ideas, and for the commenting and analysis of current world events. However, with more than 500 million tweets flowing per day, it is necessary to find efficient ways of collecting, storing, managing, mining and visualizing all this information. This is especially relevant if one considers that Twitter has no ways of indexing tweet contents, and that the only available categorization "mechanism" is the #hashtag, which is totally dependent of a user's will to use it. This paper presents an intelligent platform and framework, named MISNIS-Intelligent Mining of Public Social Networks' Influence in Society-that facilitates these issues and allows a non-technical user to easily mine a given topic from a very large tweet's corpus and obtain relevant contents and indicators such as user influence or sentiment analysis. When compared to other existent similar platforms, MISNIS is an expert system that includes specifically developed intelligent techniques that: (1) Circumvent the Twitter API restrictions that limit access to 1% of all flowing tweets. The platform has been able to collect more than 80% of all flowing portuguese language tweets in Portugal when online; (2) Intelligently retrieve most tweets related to a given topic even when the tweets do not contain the topic #hashtag or user indicated keywords. A 40% increase in the number of retrieved relevant tweets has been reported in real world case studies. The platform is currently focused on portuguese language tweets posted in Portugal. However, most developed technologies are language independent (e.g. intelligent retrieval, sentiment analysis, etc.), and technically MISNIS can be easily expanded to cover other languages and locations.

Social networks have become popular and are now becoming an alternate mean of communication, used to share information on various topics, ranging from politics or sports to simple aspects of everyday life. Twitter messages (tweets) are shared in real time and are essentially public, making them a useful source of information for areas such as tourism, marketing, health, and safety. This paper describes an information system that involves the creation and storage of a corpus of tweets, written in European Portuguese and published within the Portuguese territory. The system also involves a REST API that allows access to the stored information, and a web-based dashboard that makes it possible to analyze and visualize indicators concerning the stored data.

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