DETECTING FAKE PROFILES IN ONLINE WITH CLUSTERING TECHNIQUES IN SOCIAL MEDIA STREAMS
Main Article Content
Abstract
Leveraging clustering techniques, the study aims to enhance the identification of fraudulent activities. The proposed approach addresses the challenges of security and efficiency, offering a robust solution for tracking and mitigating the impact of fake profiles on social media. This research investigates the usability and challenges associated with Wiki blog content management systems, emphasizing natural language interfaces and sentiment analysis. Employing a Systematic Mapping Study, the study identifies key trends, challenges, and applied HumanComputer Interaction techniques in Wiki blog content management usability. It introduces Xatkit, a model-driven development framework, to address challenges and provide a higher level of abstraction in Wiki blog content management definition. The research explores sentiment analysis, proposing cross-domain sentiment classification, sentiment-sensitive thesaurus creation, and the optimization of sentiment classification using genetic algorithms. Results indicate the effectiveness of deep learning-based systems in handling emotional requests on social media. The study concludes with an overview of primary studies, highlighting the growing interest in Wiki blog content management usability. Despite advancements, the research underscores the need for further exploration and universally applicable guidelines in Wiki blog content management usability.
Downloads
Metrics
Article Details
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
You are free to:
- Share — copy and redistribute the material in any medium or format for any purpose, even commercially.
- Adapt — remix, transform, and build upon the material for any purpose, even commercially.
- The licensor cannot revoke these freedoms as long as you follow the license terms.
Under the following terms:
- Attribution — You must give appropriate credit , provide a link to the license, and indicate if changes were made . You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
- No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.
Notices:
You do not have to comply with the license for elements of the material in the public domain or where your use is permitted by an applicable exception or limitation .
No warranties are given. The license may not give you all of the permissions necessary for your intended use. For example, other rights such as publicity, privacy, or moral rights may limit how you use the material.
References
B. Nardi, S. Whittaker, and E. Bradner, ``Interaction and outeraction: Instant messaging in action,'' in Proc.
rd CSCW Conf., 2000, pp. 79_88.
R. Grinter and L. Palen, ``Instant messaging in teen life,'' in Proc. 5th CSCW Conf., 2002, pp. 21_30.
L. C. Klopfenstein, S. Delpriori, S. Malatini, and A. Bogliolo, ``The rise of bots: A survey of conversational
interfaces, patterns, and paradigms,'' in Proc. Conf. Designing Interact. Syst. (DIS), 2017, pp. 555_565.
A. Xu, Z. Liu, Y. Guo, V. Sinha, and R. Akkiraju, ``A new Wiki blog content management for customer service
on social media,'' in Proc. CHI Conf. Human Factors Comput. Syst. (CHI), 2017, pp. 3506_3510.
A. Kerly, P. Hall, and S. Bull, ``Bringing Wiki blog content management into education: Towards natural
language negotiation of open learner models,'' Knowl.-Based Syst., vol. 20, no. 2, pp. 177_185, Mar. 2007.
N. T. Thomas, ``An e-business Wiki blog content management using AIML and LSA,'' in Proc. Int. Conf. Adv.
Computing, Commun. Informat. (ICACCI), Sep. 2016, pp. 2740_2742.
V. Subrahmanian, A. Azaria, S. Durst, V. Kagan, A. Galstyan, K. Lerman, L. Zhu, E. Ferrara, A. Flammini,
and F. Menczer, ``The DARPA Twitter bot challenge,'' Computer, vol. 49, no. 6, pp. 38_46, Jun. 2016.
G. Inc, The Road to Enterprise AI. Pune, Maharashtra: RAGE Frameworks, 2017.
P. Jackson and I. Moulinier, Natural Language Processing for Online Applications: Text Retrieval, Extraction
and Categorization, vol. 5. Amsterdam, The Netherlands: John Benjamins, 2007,
M. Brambilla, M. Dosmi, and P. Fraternali, ``Model-driven engineering of service orchestrations,'' in Proc.
IEEE Congr. Services, Los Angeles, CA, USA, Jul. 2009, pp. 562_569, doi: 10.1109/SERVICES-I.2009.94.
G. Daniel, J. Cabot, L. Deruelle, and M. Derras, ``Multi-platform Wiki blog content management modeling
and deployment with the jarvis framework,'' in Advanced Information Systems Engineering (Lecture Notes in
Computer Science), vol. 11483, P. Giorgini and B. Weber, Eds. Rome, Italy: Springer, Jun. 2019, pp. 177_193,
doi: 10.1007/978-3-030-21290-2_12.
J. Masche and N.-T. Le, ``A review of technologies for conversational systems,'' in Proc. 5th ICCSAMA
Conf. Springer, 2017, pp. 212_225. [Online]. Available: https://link.springer.com/chapter/10.1007/978-3-319-
-8_19
(2018). DialogFlowWebsite.[Online]. Available: https://dialog_ow.com/ [14] (2018). Watson Assistant
Website. [Online]. Available: https://www.ibm. com/watson/ai-assistant/
J. Pereira and O. Díaz, ``Wiki blog content management dimensions that matter: Lessons from the trenches,''
in Proc. 18th ICWE Conf. Springer, 2018, pp. 129_135. [Online]. Available:
https://link.springer.com/chapter/10.1007/978-3-319- 91662-0_9
D. Kavaler, S. Sirovica, V. Hellendoorn, R. Aranovich, and V. Filkov, ``Perceived language complexity in
GitHub issue discussions and their effect on issue resolution,'' in Proc. 32nd IEEE/ACM Int. Conf. Automated
Softw. Eng. (ASE), Oct. 2017, pp. 72_83.
M. Brambilla, J. Cabot, and M. Wimmer, ``Model-driven software engineering in practice,'' Synth. Lectures
Softw. Eng., vol. 1, no. 1, pp. 1_182, Sep. 2012.