Startup Initiative Response Analysis (SIRA) Framework for Analyzing Startup Initiatives on Twitter

Bashayer Alotaibi,Rabeeh Ayaz Abbasi,Kawther Saeedi,Dimah Alahmadi,Muhammad Ahtisham Aslam

doi:10.1109/access.2020.2965181

Abstract

Social Media (SM) platforms, particularly Twitter, have become useful tools for startup companies (henceforth startups) which use the latter to support most of their business activities. As a result, there is a need to gauge the performance of specific business initiatives vis-à-vis public sentiment, or more specifically the spread of such initiatives based on Twitter user-generated content. Previous research which makes use of Twitter analysis to analyze the business activities of startups is minimal, especially for Twitter user content in the Arabic language. Consequently, this paper proposes an analytics-based framework called Startup Initiatives Response Analysis (SIRA) designed to assess the performance of initiatives launched by startups via text classification, sentiment analysis, and statistical analysis techniques. To provide empirical evidence for the viability of the proposed research framework, this paper examined the case of an Arab transportation network startup, carrying out a SIRA analysis of an initiative undertaken by Careem to empower women by encouraging them to work for the company. The results confirm the effectiveness of the proposed framework for statistically measuring the initiative spread and the public feedback based on the user-generated content on the Twitter social platform.

Highlights

Social Media Analytics (SMA) has recently emerged as an essential approach for collecting and analyzing data from social media platforms
The Confusion Matrix was used for evaluating the correctness and accuracy of classification problems where the output can be two or more classes
All the performance measures are based on the numbers inside the confusion matrix with these numbers representing the values of the four matrix elements, which are defined as: 3) EVALUATION IN TERMS OF THE PREPROCESSING STEPS PERSPECTIVE This kind of evaluation is particular to the classification models of Arabic tweets

Summary

Introduction

Social Media Analytics (SMA) has recently emerged as an essential approach for collecting and analyzing data from social media platforms. It uses advanced analytics tools and techniques to collect, process, and analyze Social Media (SM) data in order to identify useful patterns and knowledge [1]. SMA has been applied across a broad range of industries, including healthcare [2], social science [3], political science [4] and economy and business [5], [6] with a view to generating useful patterns that support various applications and activities. With increasing use of SM platforms by companies, the practice has become an essential part of many business strategies. Startups depend on such platforms to establish a strong business presence and maintain robust growth. To clarify the concept of startups in business domain, The associate editor coordinating the review of this manuscript and approving it for publication was Zhe Xiao

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