Sentiment Analysis of Breast Cancer Screening in the United States using Twitter
Kai O. Wong, Faith G. Davis, Osmar R. Zaïane, Yutaka Yasui
2016
Abstract
Whether or not U.S. women follow the recommended breast cancer screening guidelines is related to the perceived benefits and harms of the procedure. Twitter is a rich source of subjective information containing individuals’ sentiment towards public health interventions/technologies. Using our modified version of Hutto and Gilbert (2014) sentiment classifier, we described the temporal, geospatial, and thematic patterns of public sentiment towards breast cancer screening with 8 months of tweets (n=64,524) in the U.S. To examine how sentiment was related to screening uptake behaviour, we investigated and identified significant associations between breast cancer screening sentiment (via Twitter) and breast cancer screening uptake (via BRFSS) at the state level.
References
- American Cancer Society. (2015). Cancer facts and figures 2015. Atlanta: American Cancer Society.
- ArcGIS. (2015). How optimized hot spot analysis works. Environmental Systems Research Institute, Inc. URL http://desktop.arcgis.com/en/desktop/latest/tools/spati al-statistics-toolbox/how-optimized-hot-spot-analysisworks.htm.
- Austin L., Ahmad F., McNally M., Stewart D. (2002). Breast and cervical cancer screening in Hispanic women: a literature review using the health belief model. Women's Health Issues, 12, 122-128.
- Borugian M., Spinelli J., Abanto Z., Xu C., Wilkins R. (2011). Breast cancer incidence and neighbourhood income. Health Reports. Statistics Canada.
- Brooks B. (2014). Using Twitter data to identify geographic clustering of anti-vaccination sentiments. Master of Public Health, University of Washington.
- Bryson E., Schafer E., Salizzoni E., Cosgrove A., Favaro D., Dawson R. (2016). Is perception reality? Identifying community health needs when perceptions of health do not align with public health and clinical data. SM Journal of Community Medicine, 2, 1013.
- Centers for Disease Control and Prevention. (2016a). Behavioral risk factor surveillance system. Atlanta, GA: CDC. URL http://www.cdc.gov/brfss/.
- Centers for Disease Control and Prevention. (2016b). Breast cancer screening guidelines for women. Atlanta, GA: Centers for Disease Control and Prevention. URL http://www.cdc.gov/cancer/breast/pdf/BreastCancerSc reeningGuidelines.pdf.
- Coppersmith G., Dredze M., Harman C., Hollingshead K. (2015). From ADHD to SAD: analyzing the language of mental health on Twitter through self-reported diagnoses. NAACL Workshop on Computational Linguistics and Clinical Psychology.
- Cruz-Castillo A., Hernández-Valero M., Hovick S., Campuzano-González M., Karam-Calderón M., Bustamante-Montes L. (2014). A study on the knowledge, perception, and use of breast cancer screening methods and quality of care among women from central Mexico. Journal of Cancer Education.
- Dredze M. (2012). How social media will change public health. IEEE Intelligent Systems, 27, 81-84.
- Fulton J., Buechner J., Scott H., DeBuono B., Feldman J., Smith R., Kovenock D. (1991). A study guided by the health belief model of the predictors of breast cancer screening of women ages 40 and older. Public Health Reports, 106, 410-420.
- HealthTalkOnline. (2013). Reasons for not attending breast screening. URL http://www.healthtalk.org/peoplesexperiences/cancer/breast-screening/reasons-notattending-breast-screening.
- Hutto C., Gilbert E. (2014). VADER: a parsimonious rulebased model for sentiment analysis of social media text. Association for the Advancement of Artificial Intelligence.
- Janz N., Becker M. (1984). The health belief model: a decade later. Health Education Quarterly, 11, 1-47.
- Kumar S., Morstatter F., Liu H. (2013). Twitter data analytics, Springer.
- Lapointe L., Ramaprasad J., Vedel I. (2014). Creating health awareness: a social media enabled collaboration. Health and Technology.
- Mahamoud A. (2014). Breast cancer screening in racialized women: implications for health equity. Advancing Urban Health. Wellesley Institute.
- Mai V., Sullivan T., Chiarelli A. (2009). Breast cancer screening program in Canada: successes and challenges. Salud Publica Mex, 51, S228-S235.
- MapOfUSA. (2007). US population density map. URL http://www.mapofusa.net/us-population-densitymap.htm.
- MapQuest. (2014). Geocoding API. URL https://developer.mapquest.com/products/geocoding.
- Mitra T., Counts S., Pennebaker J. (2016). Understanding anti-vaccination attitudes in social media. Tenth International AAAI Conference on Web and Social Media. AAAI.
- Myers E., Moorman P., Gierisch J., Havrilesky L., Grimm L., Ghate S., Davidson B., Mongtomery R., Crowley M., McCrory D., Kendrick A., Sanders G. (2015). Benefits and harms of breast cancer screening: a systematic review. JAMA, 314, 1615-1634.
- Nakhasi A., Passarella R., Bell S., Paul M., Dredze M., Pronovost P. (2012). Malpractice and malcontent: analyzing medical complaints in Twitter. AAAI Fall Symposium on Information Retrieval and Knowledge Discovery in Biomedical Text.
- Pang B., Lee L. (2008). 4.1.2 Subjectivity detection and opinion identification. Opinion mining and sentiment analysis. Now Publishers Inc.
- Passarella R., Nakhasi A., Bell S., Paul M., Pronovost P., Dredze M. (2012). Twitter as a source for learning about patient safety events. Annual Symposium of the American Medical Informatics Association (AMIA).
- Paul M., Dredze M. (2011). You are what you tweet: analyzing Twitter for public health. International Conference on Weblogs and Social Media (ICWSM).
- Paul M., Dredze M., Broniatowski D., Generous N. (2015). Worldwide influenza surveillance through Twitter. AAAI Workshop on the World Wide Web and Public Health Intelligence.
- PewResearchCenter. (2015). Social media update 2014. Pew Research Center. URL http:// www.pewinternet.org/2015/01/09/social-mediaupdate-2014/.
- Pulman S. (2014). Multi-dimensional sentiment analysis. Oxford: Dept. of Computer Science, Oxford University. URL http://www.ltinnovate.org/sites/default/files/lt_accelerate_files/13.3 0%20Stephen_Pulman_UNIV_OXFORD.pdf.
- Smith M., Broniatowski D., Paul M., Dredze M. (2015). Tracking public awareness of influenza through Twitter. 3rd International Conference on Digital Disease Detection (DDD).
- Sugawara Y., Narimatsu H., Hozawa A., Shao L., Otani K., Fukao A. (2012). Cancer patients on Twitter: a novel patient community on social media. BMC Research Notes, 5, 699.
- Thackeray R., Burton S., Giraud-Carrier C., Rollins S., Draper C. (2013). Using Twitter for breast cancer prevention: an analysis of breast cancer awareness month. BMC Cancer, 13, 508.
- Twitter. (2014). Geo guidelines. Twitter. URL https://dev.twitter.com/overview/terms/geo-developerguidelines.
- Vance K., Howe W., Dellavalle R. (2009). Social internet sites as a source of public health information. Dermatologic Clinics, 27, 133-136.
- Wang W., Hsu S., Wang J., Huang L., Hsu W. (2014). Survey of breast cancer mammography screening behaviors in Eastern Taiwan based on a health belief model. Kaohsiung Journal of Medical Sciences, 30, 422-427.
- Zhao D., Rosson M. (2009). How and why people Twitter: the role that micro-blogging plays in informal communication at work. 243-252.
Paper Citation
in Harvard Style
Wong K., Davis F., Zaïane O. and Yasui Y. (2016). Sentiment Analysis of Breast Cancer Screening in the United States using Twitter . In Proceedings of the 8th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: KDIR, (IC3K 2016) ISBN 978-989-758-203-5, pages 265-274. DOI: 10.5220/0006047102650274
in Bibtex Style
@conference{kdir16,
author={Kai O. Wong and Faith G. Davis and Osmar R. Zaïane and Yutaka Yasui},
title={Sentiment Analysis of Breast Cancer Screening in the United States using Twitter},
booktitle={Proceedings of the 8th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: KDIR, (IC3K 2016)},
year={2016},
pages={265-274},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006047102650274},
isbn={978-989-758-203-5},
}
in EndNote Style
TY - CONF
JO - Proceedings of the 8th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: KDIR, (IC3K 2016)
TI - Sentiment Analysis of Breast Cancer Screening in the United States using Twitter
SN - 978-989-758-203-5
AU - Wong K.
AU - Davis F.
AU - Zaïane O.
AU - Yasui Y.
PY - 2016
SP - 265
EP - 274
DO - 10.5220/0006047102650274