Session
Computer Science and Communication Engineering
Description
This paper presents some advantages of using social media and social networks as an efficient way of Central Banks communication with target audience. The statistics given in this paper presents some leading banks based on number of followers on Twitter in 2018, showing that Indonesia’s Central Bank has more Twitter followers than any other monetary authority, beating out the Banco de Mexico, Federal Reserve, European Central Bank and Reserve Bank of India. In this paper some prediction of number of Twitter followers in Central Bank communication is also contributed, based on Weighted Least Squares method. An algorithm is implemented in MATLAB, while weights are used to minimize the error between the predicted and actual output sequence, presented with number of followers for each bank.
Keywords:
Social networks, Central Bank, Weighted Least Squares method, Facebook/Twitter accounts
Session Chair
Bertan Karahoda
Session Co-Chair
Krenare Pireva
Proceedings Editor
Edmond Hajrizi
ISBN
978-9951-437-69-1
Location
Pristina, Kosovo
Start Date
27-10-2018 10:45 AM
End Date
27-10-2018 12:15 PM
DOI
10.33107/ubt-ic.2018.83
Recommended Citation
Bjelobaba, Goran; Savic, Ana; Veselinovic, Radosav; and Stefanovic, Hana, "An implementation of Weighted Least Squares method in Central Bank Twitter Accounts Grew prediction" (2018). UBT International Conference. 83.
https://knowledgecenter.ubt-uni.net/conference/2018/all-events/83
An implementation of Weighted Least Squares method in Central Bank Twitter Accounts Grew prediction
Pristina, Kosovo
This paper presents some advantages of using social media and social networks as an efficient way of Central Banks communication with target audience. The statistics given in this paper presents some leading banks based on number of followers on Twitter in 2018, showing that Indonesia’s Central Bank has more Twitter followers than any other monetary authority, beating out the Banco de Mexico, Federal Reserve, European Central Bank and Reserve Bank of India. In this paper some prediction of number of Twitter followers in Central Bank communication is also contributed, based on Weighted Least Squares method. An algorithm is implemented in MATLAB, while weights are used to minimize the error between the predicted and actual output sequence, presented with number of followers for each bank.