Using sentiment analysis and topic modeling in assessing the impact of police “signaling” on investigative and prosecutorial outcomes in sexual assault reports.

Rachel Elizabeth Lovell; Joanna Klingenstein; Jiaxin Du; Laura Overman; Danielle Sabo; Daniel J Flannery; Xinyue Ye

Using sentiment analysis and topic modeling in assessing the impact of police “signaling” on investigative and prosecutorial outcomes in sexual assault reports.

Rachel Elizabeth Lovell
, Joanna Klingenstein
, Jiaxin Du
, Laura Overman
, Danielle Sabo
, Daniel J Flannery
, Xinyue Ye

Criminology and Sociology

Research output: Other contribution

Original language	English
Volume	December
State	Published - 2022

Publication series

Name	Final Research Report, National Institute of Justice

Cite this

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title = "Using sentiment analysis and topic modeling in assessing the impact of police “signaling” on investigative and prosecutorial outcomes in sexual assault reports.",

author = "Lovell, \{Rachel Elizabeth\} and Joanna Klingenstein and Jiaxin Du and Laura Overman and Danielle Sabo and Flannery, \{Daniel J\} and Xinyue Ye",

year = "2022",

language = "English",

volume = "December",

series = "Final Research Report, National Institute of Justice",

type = "Other",

}

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T1 - Using sentiment analysis and topic modeling in assessing the impact of police “signaling” on investigative and prosecutorial outcomes in sexual assault reports.

AU - Lovell, Rachel Elizabeth

AU - Klingenstein, Joanna

AU - Du, Jiaxin

AU - Overman, Laura

AU - Sabo, Danielle

AU - Flannery, Daniel J

AU - Ye, Xinyue

PY - 2022

Y1 - 2022

UR - https://www.ojp.gov/pdffiles1/nij/grants/306955.pdf

M3 - Other contribution

VL - December

T3 - Final Research Report, National Institute of Justice

ER -

Using sentiment analysis and topic modeling in assessing the impact of police “signaling” on investigative and prosecutorial outcomes in sexual assault reports.

Publication series

Other files and links

Cite this