Amir Hossein Aghaei; alireza hatami; Datis Khajeheian
Abstract
In today's digital age, it is undeniable that internet penetration rates continue to rise, and social media's influence has transformed consumers into content creators. Brands and businesses ...
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In today's digital age, it is undeniable that internet penetration rates continue to rise, and social media's influence has transformed consumers into content creators. Brands and businesses recognize the opportunity to connect with their key stakeholders through social media to avoid potential risks. The atmosphere of social media platforms and the ability to analyze audience engagement methods have become essential for brands to navigate this landscape successfully. Digikala, as the leading online retail platform in Iran, takes advantage of the potential of diverse social media channels to realize its objectives. Furthermore, the unique and general atmosphere predominant on Twitter, a microblogging platform, necessitates a nuanced understanding of user interaction. In light of these considerations, the present research aims to analyze the way in which the audience-customers engage with the Digikala brand on Twitter. The objective of the research is applied and exploratory in nature. A quantitative approach has been utilized, complemented by data mining and network analysis of social networks. The hashtag platform, a social media monitoring tool, has been utilized to collect and analyze data, specifically focusing on internet-sourced tweets. In the scope of this study, the initial step involved gathering tweets from Twitter users that contained keywords pertaining to Digikala. Following the analysis of these tweets, an attempt was made to discern the patterns reflecting audience-customer engagement with the brand. To conclude, a time series chart of the content publishing process, time series and trend of emotions or sentiments pertaining to the content, keywords, and super hashtags, as well as the topic modeling of the data collected were illustrated. Additionally, the most prominent trends and topics observed in the engagement of Twitter users with the Digikala brand were pinpointed.
Extended Abstract:
Introduction
Based on the report from the Zelka platform, Digikala is considered the most responsive Iranian brand across various social media channels. Furthermore, a notable volume of tweets incorporating the keyphrase "Digikala" are published daily on Twitter, underscoring the importance of analyzing the manner in which audience-customers engage with the Digikala brand on the Twitter platform. We firmly believe that the results obtained through this research can serve as a valuable basis for studies of comparable natures. In this research endeavor, through an in-depth examination of the various ways in which audience-customers interact with the Digikala brand, which stands as one of the most prominent online retailers within the broader Middle East region, we aim to unveil distinct perspectives pertaining to the engagement of the Twitter audience with this particular brand. Additionally, we seek to compile and present these insights in the form of descriptive and targeted charts for a comprehensive understanding of the subject.
In summary, this research aims to examine and analyze certain indicators, such as sentiment analysis, variations in the volume of published material, and the utilization of visual presentations like graphs that showcase the volume of tweets within extensive timeframes. Furthermore, this study will utilize techniques such as hashtag cloud, word cloud, and topic modeling to unveil the patterns and motivations behind audience-customer engagement with the online retail brand. Ultimately, the findings of this research will provide researchers, social network activists, particularly media managers within businesses, with a more precise understanding of the dynamics prevailing in social networks, particularly on Twitter. To obtain data from Twitter and gather tweets containing the keyword "Digikala", the tweets sent between April 1, 2021, and February 1, 2021, have been examined, resulting in a total of 96,635 tweets. Following this, by utilizing time series analysis, sentiment analysis, publishing trends and content volume, hyperwords, super hashtags, and topic modeling, we aim to extract distinguishable patterns that contribute to achieving the objectives of this research.
Methods
This research project possesses an applied and exploratory nature. In relation to the aims and purposes of the study, the research will rely primarily on quantitative data. In order to identify the patterns of customer-audience engagement concerning the Digikala brand on Twitter, we will collect and analyze tweets originating from the Digikala user account, as well as tweets from other users containing the keyphrase "Digikala". Furthermore, the utilization of data mining techniques and social network analysis have been employed, with the application of the hashtag platform, a tool for monitoring various social networks, to efficiently collect and study data (tweets) sourced from the Internet.
The official Twitter page of DigiKala, which features a blue tick and goes by the handle @digikala.com, has amassed over 35,000 followers at the time of writing this text. The page has emerged as one of the most prominent brand pages in Persian language Twitter. As such, the results of the analyses and patterns derived in this research are anticipated to be both enlightening and of practical value to other professionals and researchers within this domain.
Discussion and Results
In the course of analyzing the data, a variety of graphs and patterns pertaining to time series, sentiment analysis, and super words were obtained. Utilizing the topic modeling technique, further insights were derived. For instance, the outcome of the examination of the volume of content published on Twitter related to DigiKala highlights that utilizing this platform as part of a marketing strategy to engage the audience-customers is a shrewd move by the brand. Remarkably, during the period in which DigiKala implemented diverse Twitter campaigns, the level of engagement between the audience-customers and this brand has reached its pinnacle.
Conclusions
Following the process of gathering data and listening to the social discourse, the subsequent step involves identifying patterns related to the audience-customers. For instance, as revealed in the current research, DigiKala's audience-customers demonstrated engagement with the brand through reactions to its campaigns, festivals, gamifications, and awards on Twitter. Such engaging campaigns can serve as an effective communication model for numerous other brands.
Ultimately, while audience-customer engagement is crucial for brands, achieving an advantageous position in the spread of positive sentiments about the brand carries even greater significance. It is inevitable that businesses, regardless of their location, are not immune to errors. However, it is highly unlikely that a business with fundamental flaws can maintain its audience-customers' satisfaction and contentment. As a result, businesses and brands are able to reach the ultimate stage, which is transformation, by employing social network analysis tools and undergoing the prior steps. Reforms that transpire in regards to trends, products, methods, strategies, and so on, as well as their subsequent implementation, necessitate critical thinking and the ability to scrutinize the surrounding environment.
