利用Twitter趋势主题丰富数据库知识

C. Vassilakis, Dimitra Maniataki, George Lepouras, Angeliki Antoniou, D. Spiliotopoulos, V. Poulopoulos, Manolis Wallace, Dionisis Margaris
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引用次数: 0

摘要

每天,许多人至少使用一个社交网络(或社交媒体)账户。技术的快速发展推动了这一发展,使智能手机和移动数据更容易获得,价格也更便宜。因此,社交网络用户数量增长迅速,全球活跃用户超过10亿。易用性,以及不受空间和时间限制的交流能力,支撑了社交网络的迅速普及,以及它们被公众广泛接受。这种受欢迎程度影响了人们对许多问题的看法,塑造了消费者的习惯和行为、情绪等。许多跨学科的科学家的工作都集中在从不同的角度研究社交媒体,包括市场营销、新闻和社会学。本文研究了如何使用社交媒体的趋势信息来匹配文化数据库索引中的感兴趣主题。在此过程中确定的比赛然后被提交给文化场馆管理员,他们可以审查比赛,将其标记为有用或拒绝,并利用它们完成各种任务,最明显的是用于推广场馆及其内容。更具体地说,我们开发了一个应用程序,它收集了10个最受欢迎的twitter趋势,然后将它们的内容与给定文化数据库的内容进行匹配。使用此匹配的结果,可以向用户推荐数据库中可能与当前问题相关的项目。因此,这些匹配在经过管理员的检查和批准后,可以用来吸引目标受众的兴趣,突出显示当前问题与数据库项目的相关性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Database Knowledge Enrichment Utilizing Trending Topics from Twitter
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.
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