Using Twitter messages published online from October 2018 to June 2019, and opinion mining (OM) technology, the current study analyzes the geographic sentiments toward police in 82 metropolitan areas within the United States. Building on the frameworks of the neighborhood social contextual models, the construct validity of “sentiment toward the police” is assessed via its relationship with the features of various metropolitan areas. Results of the regression analysis indicate that the violent crime rate, racial heterogeneity, and economic disadvantage significantly affect sentiment toward the police. Our results suggest that opinion mining of social media can be an important instrument to understand public sentiment toward the police.
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Apple, N., & O’Brien, D. (1983). Neighborhood racial composition and residents’ evaluation of police performance. Journal of Police Science and Administration, 11(1), 76–84.
Berthelot, E. R., McNeal, B. A., & Baldwin, J. M. (2018). Relationships between agency-specific contact, victimization type, and trust and confidence in the police and courts. American Journal of Criminal Justice, 43(4), 768–791.
Blau, P. M. (1977). Inequality and heterogeneity: A primitive theory of social structure (Vol. 7). New York: Free Press.
Bolger, M. A., Lytle, D. J., & Bolger, P. C. (2021). What matters in citizen satisfaction with police: A meta-analysis. Journal of Criminal Justice, 72, 101760.
Bollen, J., Mao, H., & Zeng, X. (2011). Twitter mood predicts the stock market. Journal of Computational Science, 2(1), 1–8.
Brandl, S. G., Frank, J., Worden, R. E., & Bynum, T. S. (1994). Global and specific attitudes toward the police: Disentangling the relationship. Justice Quarterly, 11(1), 119–134.
Brown, B., & Benedict, W. R. (2002). Perceptions of the police. Policing: An International Journal of Police Strategies & Management., 25(3), 543–580.
Browning, S. L., & Cao, L. (1992). The impact of race on criminal justice ideology. Justice Quarterly, 9(4), 685–701.
Callegaro, M., & Yang, Y. (2018). The role of surveys in the era of “big data”. In D. Vannette & J. Krosnick (Eds.), The Palgrave handbook of survey research (pp. 175–192). Cham: Palgrave Macmillan.
Cao, L. (2011). Visible minorities and confidence in the police. Canadian Journal of Criminology and Criminal Justice, 53(1), 1–26.
Cao, L., Frank, J., & Cullen, F. T. (1996). Race, community context and confidence in the police. American Journal of Police, 15(3), 3–22.
Cao, L., & Stack, S. (2005). Confidence in the police between America and Japan. Policing: An International Journal of Police Strategies & Management, 28(1), 139–151.
Dai, M., & Jiang, X. (2016). A comparative study of satisfaction with the police in the United States and Australia. Australian & New Zealand Journal of Criminology, 49(1), 30–52.
Dai, M., & Johnson, R. R. (2009). Is neighborhood context a confounder? Policing: An International Journal of Police Strategies & Management, 32(4), 595–612.
Dave, K., Lawrence, S., & Pennock, D. M. (2003). Mining the peanut gallery: Opinion extraction and semantic classification of product reviews. In: Proceedings of the 12th International Conference on World Wide Web (pp. 519–528).
Davies, P., & Francis, P. (2018). Doing criminological research. Thousand Oaks, CA: SAGE.
Ferguson, A. G. (2019). The rise of big data policing: Surveillance, race, and the future of law enforcement. New York, NY: NYU Press.
Flexon, J. L., Lurigio, A. J., & Greenleaf, R. G. (2009). Exploring the dimensions of trust in the police among Chicago juveniles. Journal of Criminal Justice, 37(2), 180–189.
Gau, J. M., & Brunson, R. K. (2010). Procedural justice and order maintenance policing: A study of inner-city young men’s perceptions of police legitimacy. Justice Quarterly, 27(2), 255–279.
Hecht, B., Hong, L., Suh, B., & Chi, E. H. (2011, May). Tweets from Justin Bieber's heart: the dynamics of the location field in user profiles. In: Proceedings of the SIGCHI conference on human factors in computing systems (pp. 237–246). https://doi.org/10.1145/1978942.1978976.
Hridoy, S. A. A., Ekram, M. T., Islam, M. S., Ahmed, F., & Rahman, R. M. (2015). Localized twitter opinion mining using sentiment analysis. Decision Analytics, 2(1), 1–19.
Huang, W. W., & Vaughn, M. S. (1996). Support and confidence: Public attitudes toward the police. In T. J. Flanagan & D. R. Longmire (Eds.), Americans View Crime and Justice: A National Public Opinion Survey. Thousand oaks, CA: Sage.
Jang, H., Joo, H.-J., & Zhao, J. S. (2010). Determinants of public confidence in police: An international perspective. Journal of Criminal Justice, 38(1), 57–68.
Jockers, M. L. (2017). Syuzhet: An R package for the extraction of sentiment and sentiment-based plot arcs from text. Retrieved from https://github.com/mjockers/syuzhet. Accessed 1 Mar 2019.
Lee, H. D., Boateng, F. D., Kim, D., & Binning, C. (2020). Residential stability and Trust in the Police: An understudied area of police attitudinal research. American Journal of Criminal Justice, 45(1), 88–101.
Lee, J., Zhang, Y., & Hoover, L. T. (2013). Police response to domestic violence: Multilevel factors of arrest decision. Policing: An International Journal of Police Strategies & Management, 36(1), 157–114.
Liu, B. (2012). Sentiment analysis and opinion mining. Synthesis Lectures on Human Language Technologies, 5(1), 1–167.
Liu, Y., Huang, X., An, A., & Yu, X. (2007). ARSA: A sentiment-aware model for predicting sales performance using blogs. In: Proceedings of the 30th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (pp. 607–614).
Lund, S. (2018). Good cop, bad cop?: A corpus analysis on the semantic prosody of the noun cop. Karlstads: Karlstads University.
Luo, F., Ren, L., & Zhao, J. S. (2017). The effect of micro-level disorder incidents on public attitudes toward the police. Policing: An International Journal of Police Strategies & Management, 40(2), 395–409.
Mahmud, J., Nichols, J., & Drews, C. (2014). Home location identification of twitter users. ACM Transactions on Intelligent Systems and Technology (TIST), 5(3), 1–21.
Markowitz, F. E., Bellair, P. E., Liska, A. E., & Liu, J. (2001). Extending social disorganization theory: Modeling the relationships between cohesion, disorder, and fear. Criminology, 39(2), 293–319.
Maxson, C. L., Hennigan, K., & Sloane, D. C. (2003). Factors that influence public opinion of the police. Washington, DC: US Department of Justice, Office of Justice Programs, National Institute of Justice.
Morenoff, J. D., Sampson, R. J., & Raudenbush, S. W. (2001). Neighborhood inequality, collective efficacy, and the spatial dynamics of urban violence. Criminology, 39(3), 517–558.
Nasukawa, T., & Yi, J. (2003). Sentiment analysis: Capturing favorability using natural language processing. Proceedings of the 2nd International Conference on Knowledge Capture (pp. 70–77).
O’Brien, D. T., Sampson, R. J., & Winship, C. (2015). Ecometrics in the age of big data: Measuring and assessing “broken windows” using large-scale administrative records. Sociological Methodology, 45(1), 101–147.
O’Connor, B., Balasubramanyan, R., Routledge, B., & Smith, N. (2010, May). From tweets to polls: Linking text sentiment to public opinion time series. In: Proceedings of the International AAAI Conference on Web and Social Media.
Oglesby-Neal, A., Tiry, E., & Kim, K. (2019). Public perceptions of police on social media. Washington, DC: Urban Institute.
Oh, G., Ren, L., & He, P. (2019). Social disorder and residence-based fear of crime: The differential mediating effects of police effectiveness. Journal of Criminal Justice, 63, 1–11.
Othman, R., Belkaroui, R., & Faiz, R. (2017). Extracting product features for opinion mining using public conversations in twitter. Procedia Computer Science, 112, 927–935.
Parker, K. D., Onyekwuluje, A. B., & Murty, K. S. (1995). African Americans’ attitudes toward the local police: A multivariate analysis. Journal of Black Studies, 25(3), 396–409.
Raudenbush, S. W., & Sampson, R. J. (1999). Ecometrics: toward a science of assessing ecological settings, with application to the systematic social observation of neighborhoods. Sociological methodology, 29(1), 1–41.
Reisig, M. D., & Parks, R. B. (2000). Experience, quality of life, and neighborhood context: A hierarchical analysis of satisfaction with police. Justice Quarterly, 17(3), 607–630.
Ren, L., Cao, L., Lovrich, N., & Gaffney, M. (2005). Linking confidence in the police with the performance of the police: Community policing can make a difference. Journal of Criminal Justice, 33(1), 55–66.
Sampson, R. J., & Bartusch, D. J. (1998). Legal cynicism and (subcultural?) tolerance of deviance: The neighborhood context of racial differences. Law and Society Review, 32, 777–804.
Sampson, R. J., Raudenbush, S. W., & Earls, F. (1997). Neighborhoods and violent crime: A multilevel study of collective efficacy. Science, 277(5328), 918–924.
Schafer, J. A., Huebner, B. M., & Bynum, T. S. (2003). Citizen perceptions of police services: Race, neighborhood context, and community policing. Police Quarterly, 6(4), 440–468.
Schuman, H., & Gruenberg, B. (1972). Dissatisfaction with city services: Is race an important factor? People and Politics in Urban Society, 6, 369–392.
Sharma, P., & Moh, T.-S. (2016). Prediction of Indian election using sentiment analysis on Hindi twitter. 2016 IEEE international conference on big data (big data), 1966–1971.
Skogan, W. G. (2009). Concern about crime and confidence in the police: Reassurance or accountability? Police Quarterly, 12(3), 301–318.
Smith, S. K., Steadman, G. W., Minton, T. D., & Townsend, M. (1999). Criminal victimization and perceptions of community safety in 12 cities, 1998. Washington, DC: Bureau of Justice Statistics and Office of Community Oriented Policing Services, US Department of Justice.
Sprott, J. B., & Doob, A. N. (2014). Confidence in the police: Variation across groups classified as visible minorities. Canadian Journal of Criminology and Criminal Justice, 56(3), 367–379.
Stack, S. J., & Cao, L. (1998). Political conservatism and confidence in the police: A comparative analysis. Journal of Crime and Justice, 21(1), 71–76.
Taylor, T. J., Turner, K. B., Esbensen, F.-A., & Winfree Jr., L. T. (2001). Coppin’an attitude: Attitudinal differences among juveniles toward police. Journal of Criminal Justice, 29(4), 295–305.
Tims, A. R., Fan, D. P., & Freeman, J. R. (1989). The cultivation of consumer confidence: A longitudinal analysis of news media influence on consumer sentiment. Advances in Consumer Research, 16, 758–770.
Van Craen, M. (2013). Explaining majority and minority trust in the police. Justice Quarterly, 30(6), 1042–1067.
Weitzer, R., & Tuch, S. A. (2002). Perceptions of racial profiling: Race, class, and personal experience. Criminology, 40(2), 435–456.
Weitzer, R., & Tuch, S. A. (2005). Racially biased policing: Determinants of citizen perceptions. Social Forces, 83(3), 1009–1030.
Williams, M. L., Burnap, P., & Sloan, L. (2017). Crime sensing with big data: The affordances and limitations of using open-source communications to estimate crime patterns. The British Journal of Criminology, 57(2), 320–340.
Worrall, J. L. (1999). Public perceptions of police efficacy and image: The “fuzziness” of support for the police. American Journal of Criminal Justice, 24(1), 47–66.
Wu, Y., & Sun, I. Y. (2009). Citizen trust in police: The case of China. Police Quarterly, 12(2), 170–191.
Wu, Y., Sun, I. Y., & Triplett, R. A. (2009). Race, class or neighborhood context: Which matters more in measuring satisfaction with police? Justice Quarterly, 26(1), 125–156.
Zhao, J. S., Tsai, C. F., Ren, L., & Lai, Y. L. (2014). Public satisfaction with police control of disorder crime: does the public hold police accountable? Justice Quarterly, 31(2), 394–420.
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Oh, G., Zhang, Y. & Greenleaf, R.G. Measuring Geographic Sentiment toward Police Using Social Media Data. Am J Crim Just (2021). https://doi.org/10.1007/s12103-021-09614-z
- Opinion mining
- Sentiment analysis
- Twitter messages
- Attitude towards police