Database Knowledge Enrichment Utilizing Trending Topics from Twitter
Authors: Vassilakis, Costas 
Maniataki, Dimitra 
Lepouras, George 
Antoniou, Angeliki 
Spiliotopoulos, Dimitris 
Poulopoulos, Vassilis 
Wallace, Manolis 
Margaris, Dionisis 
Issue Date: 1-Jan-2020
Conference: 2020 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2020 
Book: Proceedings of the 2020 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2020 
Keywords: Application, Business Intelligence, Extraction, Knowledge Enrichment, Processing, Social Networks, Trending Topics
Abstract: 
Every day, many people use at least one social network (or social media) account. This development has been boosted by the rapid growth of technology, making both smartphones and mobile data much more accessible and inexpensive. Therefore, the number of social networks users is growing rapidly, accounting more than 1 billion active users worldwide. The ease of use, as well as the ability to communicate without spatial and temporal restrictions underpinned the rapid increase of the popularity of social networks, as well as their wide acceptance by the general public. This popularity influences people's opinion on many issues, shapes consumer habits and behaviour, mood, etc. The work of many scientists across multiple disciplines has focused on studying social media from various perspectives, including marketing, journalism and sociology. This paper investigates how trending information from social media can be used to match topics of interest from cultural database indices. Matches identified in this process are then presented to cultural venue curators, who can then review matches, mark them as useful or reject them, and exploit them for various tasks, and most notably for the promotion of the venue and its content. More specifically, we have developed an application, which collects the 10 most popular twitter trends and then matches their content with the contents of a given cultural database. Using the results of this match, items from the database that may be related to current issues may be recommended to the user. As a result, these matches, after being inspected and approved by the administrator, can be used to attract the interest of the target audience, highlighting the correlation of current issues with the database's items.
ISBN: 9781728110561
DOI: 10.1109/ASONAM49781.2020.9381421
URI: https://uniwacris.uniwa.gr/handle/3000/608
Type: Conference Paper
Department: Department of Archival, Library and Information Studies 
School: School of Administrative, Economics and Social Sciences 
Affiliation: University of West Attica (UNIWA) 
Appears in Collections:Book Chapter / Κεφάλαιο Βιβλίου

CORE Recommender
Show full item record

SCOPUSTM   
Citations 50

1
checked on Nov 8, 2024

Page view(s)

39
checked on Nov 13, 2024

Google ScholarTM

Check

Altmetric

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.