000 02176nam a22001937a 4500
003 OSt
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008 180524b xxu||||| |||| 00| 0 eng d
040 _cIIITMK
100 _aReshma G R (92216019)
_914047
245 _aComputational analysis of sports team
300 _aMSC DA 2016-2018
500 _aThe purpose of this project is to evaluate how to sponsor a sports team by analyzing the social media profiles of teams and players. This approach is carried out through an in-depth analysis on sports marketing and the rising popularity of social media marketing for sports brands in the world. The initial data is collected for the algorithm comprises of sports team's tweets, Facebook posts, website metrics, TV viewership metrics, demographic distribution, gender distribution, age group distribution and keyword metrics. The tweet bots crawls and gathers information such as tweets, number of shares for the tweets and number of retweets from twitter for all available tweets and saves in the database along with the above mentioned metrics. The Facebook crawlers gather all information such as shares, comments, likes of posts and emotions such as love, angry, like, sad, laugh and saves in the database. Demographic distribution is the metric which shows which country follows the team's social media. This provides us valuable information on how a brand is valued across the world. Age group distribution shows what type of people follows the brand. This metric is particularly useful in giving weightage to the TV or social media metrics of the team. Gender distribution is another metric which helps to identify which gender is following the particular brand. Keyword metrics which consists of popular keywords people search for the team. We track these metrics and gathers information on the search from various sources. Generated algorithms for the calculation of index, this index tells the sponsor that which team to be sponsored based on their reach.
502 _bMSC DA
_c2016-2018
_dINT
_eDr. Manoj Kumar T K
650 _aSOCIAL MEDIA
_914048
650 _aSPORTS TEAM
_914049
650 _aMARKETING
_914050
942 _2ddc
_cPR
999 _c6059
_d6059