Social media analysis based on mobile systems

The use of internet and social media has increasing with the developing new
technologies and large number of people have actively using of the internet. At the
same time the development of mobile technologies and the widespread usage of the
mobile devices that can be shown as the reason for that. In this way, social media has
become a virtual environment in which people interact with each other.
Some of social media platforms such as Twitter have become very popular and most
of people share some information about themselves on these platforms. They also
share their ideas, thoughts, lives and much more things with other people through on
these platforms. On this thesis that is aimed to take meaningful results from the
information that people share on the Twitter platform. In this way, very useful
information can be revealed. Furthermore, can be obtained which people have shared
about a specified keyword and what they think that about it. All these references
play an important role with about people, universities, companies, events and so on.
Likewise, all these social media analyses are performed as thesis product on Android
based mobile environment and thanks to this android app, can be displayed the
important information of users who post tweet or tweets with about specified
keywords. Their locations and countries can be also displayed. The other a different
inference is what time periods of users generally post tweet on Twitter. People use
some operating systems to connect from internet to Twitter platforms and these are
mobile and desktop operation systems. Therefore, can be analysed to which
operating system is used when posting a tweet on Twitter with specified keyword.
This feature includes different results according to different keywords.
Besides all this, the information all the people in the world shared on Twitter that is
can be view on the mobile application. The main goal of at this point is to analyse all
the interactions on Twitter and as a result the getting significant results. In this way,
meaningful results can be extract and these results can be accessed with Android
mobile devices.