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<!DOCTYPE html>
<html lang="en">
<head>
<title>Human-Machine Interaction @ IIIT-D</title>
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<!-- <h1><strong>An Investigation of Fortune 100 Companies: Insights to improve Twitter Engagement</strong></h1> -->
<!-- <p class="lead mb-5">Free Web Template by <a href="#" target="_blank">Colorlib</a></p> -->
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<h3 class="text-black h1 site-section-heading">Best Practices for Better Twitter Engagement: What small and medium-sized enterprises can learn from Top Fortune 100 companies</h3>
<img src="images/tanya_kapur_proj.jpg" height="683.76" width="683.76" alt="Image" class="img-fluid rounded" >
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<p class="text-primary lead" > <strong>Abstract</strong></p>
<p class="lead" style="text-align:justify;">User engagement is an important metric to improve the connection with the users. Previous studies have analysed the utility of different Twitter parameters that increase user engagement. However, their appropriateness for user engagement has been analysed using a small number of distinct Twitter parameters and on different data sets. In addition, the effects of users’ replies on the tweets of the companies have not been analysed. In the current research, we analyse the tweets of Fortune 100 companies to assess the unified effects of parameters such as the usage of hashtags, images, mentions, emojis, text length and the sentiment of the tweet on user engagement. Using empirical analysis, we first propose an augmented engagement formula to accommodate the sentiment score of the users’ replies. Further, we perform multiple linear regression analysis to assess the effects of different parameters on the revised engagement score. We observe that the tweets with length less than 140 characters have a higher user engagement activity. Results on tweet wise analysis showed that the use of emojis while replying positively affects user engagement. In addition, the sector-wise analysis revealed that the presence of image in tweets has a positive influence on the engagement score for 66% of the sectors, followed by the hashtags, emojis, and the tweet length with 60%, 33%, and 40% sector coverage, respectively. Finally, the study provides significant recommendations that can be employed to increase user engagement.</p>
<br>
<div class="paper_links">
<p class="text-primary lead inline" class="inline"> <strong>Student Collaborator</strong></p> <p class="lead inline">:<a href="team.html#tanya-kapur" target="_blank"> Tanya Kapur (IIIT-Delhi)</a>, Anvit Sachadev (IIIT-Delhi)</p></div>
<!-- <br> -->
<!-- <p class="text-primary lead inline" class="inline"> <strong>Faculty Collaborator</strong></p> <p class="lead inline">: Pramil Panjawani (IIIT Delhi)</p> -->
<!-- <br> -->
<!-- <p class="text-primary lead inline" class="inline"> <strong>External Collaborator</strong></p> <p class="lead inline">: Satvika Anand (IIIT Delhi)</p> -->
<!-- <p class="lead"></p> -->
<!-- <p class="text-primary lead" > <strong>Publication</strong></p>
<p class="lead" style="text-align:justify;">Kumar Singh, D., Sharma, S., Shukla, J., & Eden, G. (2020, March).<a href="https://dl.acm.org/doi/abs/10.1145/3371382.3378315"><strong> <i> Toy, Tutor, Peer, or Pet? Preliminary Findings from Child-Robot Interactions in a Community School.</i></strong></a> In Companion of the 2020 ACM/IEEE International Conference on Human-Robot Interaction (pp. 325-327).<a href="https://www.youtube.com/watch?v=hMyGznAFYMk"><i><strong>[Video]</strong></i></a></p>
-->
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<h2 class="text-primary">Innovate</h2>
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Okhla Industrial Estate, Phase III, (Near Govind Puri Metro Station), New Delhi - 110020, India</p>
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<p style="text-align: justify;">At Human Machine Interaction (HMI) lab, we investigate novel interaction mechanisms to empower human-machine cooperation. Located at Indraprastha Institute of Information Technology, Delhi, HMI Lab is an initiative founded by Dr. Jainendra Shukla.</p>
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