Tag: CrimeRelated

Price: $99.00
(as of Dec 25,2024 00:20:11 UTC – Details)

Publisher ‏ : ‎ Routledge; 1st edition (June 5, 2025)
Language ‏ : ‎ English
Hardcover ‏ : ‎ 152 pages
ISBN-10 ‏ : ‎ 1032957891
ISBN-13 ‏ : ‎ 978-1032957890
Item Weight ‏ : ‎ 16 ounces

Crime-Related Events Identification Based on Text Analytics Approach

In today’s digital age, the amount of data available is vast and constantly growing. One area where this wealth of information can be particularly useful is in identifying and analyzing crime-related events. By utilizing text analytics, researchers and law enforcement agencies can extract valuable insights from large amounts of text data to better understand and prevent criminal activities.

Text analytics involves the use of natural language processing, machine learning, and other techniques to analyze and extract information from unstructured text data. This can include news articles, social media posts, police reports, and other sources of textual information.

By applying text analytics to crime-related data, researchers can identify patterns, trends, and relationships that may not be immediately apparent. For example, by analyzing social media posts, law enforcement agencies can identify potential hotspots for criminal activity or detect patterns of gang-related behavior. By analyzing news articles, researchers can track the spread of misinformation and propaganda related to crime.

Furthermore, text analytics can also be used to monitor and analyze online forums and chat rooms where criminal activities are discussed or planned. By using text analytics to identify keywords, phrases, and patterns indicative of criminal behavior, law enforcement agencies can intervene before crimes are committed.

Overall, the use of text analytics in identifying and analyzing crime-related events can provide valuable insights for law enforcement agencies, researchers, and policymakers. By harnessing the power of text analytics, we can better understand, prevent, and combat criminal activities in our communities.
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