Social media analytics for investigations: A survey of recent trends, challenges and future research direction

Sarbagya Shakya; Edgar Ceh-Varela

doi:10.29329/jsomer.57

Authors

Sarbagya Shakya Eastern New Mexico University, USA https://orcid.org/0000-0001-8897-2776
Edgar Ceh-Varela Eastern New Mexico University, USA https://orcid.org/0000-0001-6277-2741

DOI:

https://doi.org/10.29329/jsomer.57

Keywords:

sentiment analysis, natural language procesing, machine learning, crime investigations, social media analytics

Abstract

Social media analytics has emerged as a critical tool for investigations, providing valuable insights into user interactions, trends, and behaviors across various platforms. With over 4.76 billion active social media users globally, this vast data source has proven useful in government investigations and criminal litigations. However, extracting reliable information from social media presents significant challenges, including data representativeness, ethical and legal concerns, user behavior interpretation, and the growing issue of misinformation. This paper reviews recent trends in social media analytics, particularly its application in investigations, highlighting the increasing use of machine learning for data processing and analysis. Our analysis reveals its transformative impact, enabling advanced evidence collection, suspect identification, criminal network mapping, and proactive crime prevention. However, significant challenges persist regarding data validity, bias minimization, ethical responsibilities, and misinformation. Additionally, the paper offers future research directions, emphasizing the need for standardized frameworks, adaptive ethical guidelines, AI-driven real-time multimodal analysis, and robust privacy protection measures. These advancements aim to enhance the reliability and effectiveness of social media analytics for investigative purposes.

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