Computational analysis of sports team (Record no. 6059)

MARC details
000 -LEADER
fixed length control field 02176nam a22001937a 4500
003 - CONTROL NUMBER IDENTIFIER
control field OSt
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20220107122838.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 180524b xxu||||| |||| 00| 0 eng d
040 ## - CATALOGING SOURCE
Transcribing agency IIITMK
100 ## - MAIN ENTRY--PERSONAL NAME
Personal name Reshma G R (92216019)
9 (RLIN) 14047
245 ## - TITLE STATEMENT
Title Computational analysis of sports team
300 ## - PHYSICAL DESCRIPTION
Extent MSC DA 2016-2018
500 ## - GENERAL NOTE
General note The purpose of this project is to evaluate how to sponsor a sports team by analyzing the social<br/>media profiles of teams and players. This approach is carried out through an in-depth analysis on<br/>sports marketing and the rising popularity of social media marketing for sports brands in the<br/>world. The initial data is collected for the algorithm comprises of sports team's tweets, Facebook<br/>posts, website metrics, TV viewership metrics, demographic distribution, gender distribution,<br/>age group distribution and keyword metrics. The tweet bots crawls and gathers information such<br/>as tweets, number of shares for the tweets and number of retweets from twitter for all available<br/>tweets and saves in the database along with the above mentioned metrics. The Facebook crawlers<br/>gather all information such as shares, comments, likes of posts and emotions such as love, angry,<br/>like, sad, laugh and saves in the database. Demographic distribution is the metric which shows<br/>which country follows the team's social media. This provides us valuable information on how a<br/>brand is valued across the world. Age group distribution shows what type of people follows the<br/>brand. This metric is particularly useful in giving weightage to the TV or social media metrics of<br/>the team. Gender distribution is another metric which helps to identify which gender is following<br/>the particular brand. Keyword metrics which consists of popular keywords people search for the<br/>team. We track these metrics and gathers information on the search from various sources.<br/>Generated algorithms for the calculation of index, this index tells the sponsor that which team to<br/>be sponsored based on their reach.
502 ## - DISSERTATION NOTE
Degree type MSC DA
Name of granting institution 2016-2018
Year degree granted INT
-- Dr. Manoj Kumar T K
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element SOCIAL MEDIA
9 (RLIN) 14048
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element SPORTS TEAM
9 (RLIN) 14049
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element MARKETING
9 (RLIN) 14050
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme Dewey Decimal Classification
Koha item type
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Collection code Home library Current library Shelving location Date acquired Total Checkouts Barcode Date last seen Price effective from Koha item type
    Dewey Decimal Classification     Non Fiction IIITM-K Kerala University of Digital Sciences, Innovation and Technology Knowledge Centre   24/05/2018   R-1366 24/05/2018 24/05/2018 Project Reports