Skip to main content

Advanced Search

Projected result for your current search: 0

Search Operators:

You can use operators in your search query to narrow down your results even more. Click on the search operator to see an explanation of how it works.
Finds documents with exactly this word group, in exactly this word order and spelling (e.g. "employer branding").
Finds documents with both search terms (e.g. sales AND bonus).
Finds documents with one or the other search term (e.g. porsche OR volkswagen).
Finds documents with all search terms. Blank space is understood as AND (e.g. man robot production).
Finds documents with no appearance of the word behind NOT (e.g. ford NOT "harrison ford").
Finds documents where the search term is mentioned at least "n" times."n" may be any number (e.g. COUNT(gear)>8).
Finds documents with both search terms in any word order, permitting "n" words as a maximum distance between them. Best choose between 15 and 30 (e.g. NEAR(recruit, professionals, 20)).
Finds documents with the search term in word versions or composites. The asterisk * marks whether you wish them BEFORE, BEHIND, or BEFORE and BEHIND the search term (e.g. lightweight*, *lightweight, *lightweight*).
Finds documents with the search term in different spellings. "?" allows only one character (e.g. organi?ation).
Special characters are understood as AND (e.g. Miller Bros. & Sons).

Semantic Search

powered by (Link opens in a new window)
loading …
Log in
Top

Empowering Social Media Engagement: A Web Application for Analyzing and Categorizing Digital Content

  • 2026
  • OriginalPaper
  • Chapter
Published in:
Authors
Rokkam Vivek Vardhan Reddy
Vidiyala Abhiram
Alwala Raghavendra Goud
M. V. S. Sai Teja
Sree Lakshmi Pinapatruni
Pavan Kumar Pagadala
Published in
Proceedings of the 7th International Conference on Communications and Cyber Physical Engineering
Publisher
Springer Nature Singapore

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

This chapter delves into the transformative potential of social media data analysis, showcasing how digital content can be categorized and visualized to uncover meaningful patterns. The study explores various datasets from popular platforms like Instagram, Snapchat, Facebook, and YouTube, highlighting user activities and behaviors. Through data visualization techniques, the chapter provides insights into how social media engagement can be leveraged for marketing, education, and team-building strategies. The research methodology involves data collection, preprocessing, and analysis using tools like Pandas, NumPy, and Matplotlib, followed by visualization using Tableau. The results are presented through clear and informative charts, offering a comprehensive overview of user engagement across different platforms. The conclusion emphasizes the broader implications of social media data analysis, suggesting its potential to influence various sectors and enhance decision-making processes. This chapter serves as a valuable resource for professionals seeking to understand and harness the power of social media data.
AI Generated

This summary of the content was generated with the help of AI.

Already a customer? Then log in here to gain access.

Customer login

Not a customer yet? Then find out more about our access models now:

Individual Access

Start your personal individual access now. Get instant access to more than 164,000 books and 540 journals – including PDF downloads and new releases.

Starting from 54,00 € per month!    

Get access

Access for Businesses

Utilise Springer Professional in your company and provide your employees with sound specialist knowledge. Request information about corporate access now.

Find out how Springer Professional can uplift your work!

Contact us now

For explorers: Get to know our platforms better with a free registration.

Register for free
previous chapter Empowering Indian Farmers: A Machine Learning Approach for Optimal Crop Selection and Sustainable Agriculture
next chapter Synergizing Literature Insights and Deep Learning for Effective Skin Cancer Detection and Classification
Title
Empowering Social Media Engagement: A Web Application for Analyzing and Categorizing Digital Content
Authors
Rokkam Vivek Vardhan Reddy
Vidiyala Abhiram
Alwala Raghavendra Goud
M. V. S. Sai Teja
Sree Lakshmi Pinapatruni
Pavan Kumar Pagadala
Copyright Year
2026
Publisher
Springer Nature Singapore
Book
Proceedings of the 7th International Conference on Communications and Cyber Physical Engineering

Print ISBN: 978-981-9502-68-4

Electronic ISBN: 978-981-9502-69-1

Copyright Year: 2026

DOI
https://doi.org/10.1007/978-981-95-0269-1_128
This content is only visible if you are logged in and have the appropriate permissions.