Framework for Social Media Analysis Based on Hashtag Research
Source abstract
Abstract
Social networks have become a common part of many people’s daily lives. Users spend more and more time on these platforms and create an active and passive digital footprint through their interaction with other subjects. These data have high research potential in many fields, because understanding people’s communication on social media is essential to understanding their attitudes, experiences and behaviours. Social media analysis is a relatively new subject. There is still a need to develop methods and tools for researchers to help solve typical problems associated with this area. A researcher will be able to focus on the subject of research entirely. This article describes the Social Media Analysis based on Hashtag Research (SMAHR) framework, which uses social network analysis methods to explore social media communication through a network of hashtags. The results show that social media analysis based on hashtags provides information applicable to theoretical research and practical strategic marketing and management applications.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Digital Marketing and Social Media · Sentiment Analysis and Opinion Mining · Complex Network Analysis Techniques
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Management, Faculty of Economics and Management, Czech University of Life Sciences Prague, 165 21 Prague, Czech Republic
Department of Systems Engineering, Faculty of Economics and Management, Czech University of Life Sciences Prague, 165 21 Prague, Czech Republic
Funding
Faculty of Economics and Management CULS Prague
References (76)
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