ISSN2320-2882
Impact Factor9.17
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ESTD2013
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Paper Title
Python-Powered Solutions for Managing and Analyzing Unstructured Social Media Big Data
Authors
Dr. Lata V. Upadhyay.
Keywords
Big Data, Data Analysis, Natural Language Processing, Python, Sentiment Analysis, Social Media, Social Network Analysis, Topic Modeling, Trend Detection, Unstructured Data
Abstract
Large volumes of unstructured data are produced by social media platforms, which make it difficult for governments, corporations, and researchers to glean valuable insights. The potential of Python-powered solutions for handling, processing, and evaluating large amounts of unstructured social media data is examined in this study. We look at the main Python libraries, tools, and technologies that make it possible to handle massive amounts of social media data effectively. Organizations can use Python's capabilities to optimize their content strategy, drive decision-making, and analyze customer sentiment by gaining insightful information from social media.
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IJCRT — journal style
"Python-Powered Solutions for Managing and Analyzing Unstructured Social Media Big Data", IJCRT - International Journal of Creative Research Thoughts (www.ijcrt.org), ISSN:2320-2882, Vol.14, Issue 6, page no.f529-f533, June 2026, Available :https://ijcrt.org/papers/IJCRT2606595.pdf
APA — 7th edition
Upadhyay., L. V. (2026). Python-Powered Solutions for Managing and Analyzing Unstructured Social Media Big Data. International Journal of Creative Research Thoughts, 14(6), f529-f533. https://doi.org/10.56975/ijcrt.v14i6.299373
MLA — 9th edition
Upadhyay., Lata V. "Python-Powered Solutions for Managing and Analyzing Unstructured Social Media Big Data." International Journal of Creative Research Thoughts, vol. 14, no. 6, 2026, pp. f529-f533, https://doi.org/10.56975/ijcrt.v14i6.299373.
Chicago — 17th, bibliography
Upadhyay., Lata V. "Python-Powered Solutions for Managing and Analyzing Unstructured Social Media Big Data." International Journal of Creative Research Thoughts 14, no. 6 (2026): f529-f533. https://doi.org/10.56975/ijcrt.v14i6.299373.
Harvard — author–date
Upadhyay., L.V. (2026) 'Python-Powered Solutions for Managing and Analyzing Unstructured Social Media Big Data', International Journal of Creative Research Thoughts, 14(6), pp. f529-f533. Available at: https://doi.org/10.56975/ijcrt.v14i6.299373
IEEE — numbered reference
L. V. Upadhyay., "Python-Powered Solutions for Managing and Analyzing Unstructured Social Media Big Data," IJCRT, vol. 14, no. 6, pp. f529-f533, Jun. 2026, doi: 10.56975/ijcrt.v14i6.299373.
Vancouver — biomedical
Upadhyay. LV. Python-Powered Solutions for Managing and Analyzing Unstructured Social Media Big Data. IJCRT. 2026 Jun;14(6):f529-f533. doi: 10.56975/ijcrt.v14i6.299373
AMA — 11th edition
Upadhyay. LV. Python-Powered Solutions for Managing and Analyzing Unstructured Social Media Big Data. IJCRT. 2026;14(6):f529-f533. doi:10.56975/ijcrt.v14i6.299373
BibTeX — Zotero, Mendeley, LaTeX
@article{IJCRT2606595,
author = {Lata V. Upadhyay.},
title = {Python-Powered Solutions for Managing and Analyzing Unstructured Social Media Big Data},
journal = {International Journal of Creative Research Thoughts},
volume = {14},
number = {6},
pages = {f529-f533},
year = {2026},
month = {June},
issn = {2320-2882},
doi = {10.56975/ijcrt.v14i6.299373},
url = {https://doi.org/10.56975/ijcrt.v14i6.299373}
}
RIS — EndNote, RefWorks
TY - JOUR
AU - Upadhyay., Lata V.
TI - Python-Powered Solutions for Managing and Analyzing Unstructured Social Media Big Data
T2 - International Journal of Creative Research Thoughts
JA - IJCRT
VL - 14
IS - 6
PY - 2026
SN - 2320-2882
DO - 10.56975/ijcrt.v14i6.299373
UR - https://doi.org/10.56975/ijcrt.v14i6.299373
SP - f529-f533
ER -
Issue
Volume 14 Issue 6,
June-2026
Pages : f529-f533
Article Information
- Pages
- f529-f533
- Published
- June 2026
- Registration ID
- IJCRT_299373
- Published Paper ID
- IJCRT2606595
- Research Area
- Science and Technology
- Author Type
- Indian Author
- Location
- Rajkot, Gujarat, India
- Peer Review
- Request Peer Review Report
- Licence
- CC BY 4.0 · Open Access
- ISSN & Impact Factor
- 2320-2882 · IF 9.17
- Downloads
- 223
- Permanent Link
- https://ijcrt.org/viewpaperforall.php?paper=IJCRT2606595
- Published Paper PDF
- https://ijcrt.org/papers/IJCRT2606595.pdf
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International Journal of Creative Research Thoughts
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2320-2882
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Acknowledgements
The authors would like to thank the reviewers and the editorial board of International Journal of Creative Research Thoughts for their careful reading and constructive comments, and all colleagues who supported the preparation of this manuscript.
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