Initial Exploration on an Effective Social Media Analytics Method and Algorithm for Instagram Hashtags

Nurul Atikah Ahmad Rosli, M. Husin
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引用次数: 2

Abstract

Over the years, social media has brought many benefits to different fields, especially in the business sector. Most of the existing organizations have taken these benefits to actively engage with the public to increase their online business value. The use of hashtags on numerous social media platforms especially on Instagram is one of the highly used benefits. By tagging specific postings, business organizations are able to promote and communicate with their customers directly in a more interactive manner. In this article, the authors are exploring the following: (1) to determine the effectiveness of the existing analytics method (text identification and trend analysis) for analyzing Instagram hashtag data and; (2) to determine the effectiveness of existing analytic techniques such as Naïve Bayes and Support Vector Machines (SVM) suited for the selected analytics method. As a result, the authors have identified that the combination of Trend Analysis method and SVM are an effective social media analytics approach for analyzing Instagram hashtag data.
Instagram标签有效的社交媒体分析方法与算法初探
多年来,社交媒体给不同领域带来了许多好处,尤其是在商业领域。大多数现有的组织都利用这些优势积极地与公众接触,以增加他们的在线业务价值。在众多社交媒体平台上使用标签,尤其是在Instagram上,是一个被广泛使用的好处。通过标记特定的帖子,商业组织能够以更具互动性的方式直接促进和与客户沟通。在本文中,作者正在探索以下内容:(1)确定现有分析方法(文本识别和趋势分析)用于分析Instagram标签数据和的有效性;(2)确定现有分析技术的有效性,如Naïve贝叶斯和支持向量机(SVM)适合所选的分析方法。因此,作者已经确定趋势分析方法和支持向量机的组合是一种有效的分析Instagram标签数据的社交媒体分析方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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