Two studies on twitter networks and tweet content in relation to amyotrophic lateral sclerosis (ALS): Conversation, information, and 'diary of a daily life'

Studies in Health Technology and Informatics

Volumn 227, Issue , 2016, Pages 41-47

  Hemsley, Bronwyn ^a   Palmer, Stuart ^b  

^a UNIVERSITY OF NEWCASTLE   (Australia)

^b DEAKIN UNIVERSITY   (Australia)

Author keywords

Amyotrophic Lateral Sclerosis; Motor Neurone Disease; Severe Communication Disability; Tweet Content; Twitter; Twitter Research

Indexed keywords

HEALTH CARE; HYBRID INTEGRATED CIRCUITS; SOCIAL NETWORKING (ONLINE);

AMYOTROPHIC LATERAL SCLEROSIS; MOTOR NEURONE DISEASE; SEVERE COMMUNICATION DISABILITY; TWEET CONTENT; TWITTER;

NEURODEGENERATIVE DISEASES;

AMYOTROPHIC LATERAL SCLEROSIS; CLASSIFICATION; COMMUNICATION DISORDER; EMOTION; HUMAN; INFORMATION DISSEMINATION; INTERPERSONAL COMMUNICATION; MIDDLE AGED; PSYCHOLOGY; SOCIAL MEDIA;

AMYOTROPHIC LATERAL SCLEROSIS; COMMUNICATION; COMMUNICATION DISORDERS; EMOTIONS; HUMANS; INFORMATION DISSEMINATION; MIDDLE AGED; SOCIAL MEDIA;

EID: 84982143983     PISSN: 09269630     EISSN: 18798365     Source Type: Book Series    
DOI: 10.3233/978-1-61499-666-8-41     Document Type: Conference Paper

References (13)

1. Neiger BL, Thackeray R, Burton SH, Thackeray CR, Reese, JH. (2013) Use of Twitter among local health departments: an analysis of information sharing, engagement, and action. Journal of Medical Internet Research, 2013, Aug 15(8) e177.
2. Hemsley, B., Palmer, S., & Balandin, S. (2014). Tweet reach: A research protocol for using Twitter to increase information exchange in people with communication disabilities. Developmental Neurorehabilitation, 17, 84-89.
3. Hemsley B, Dann S, Palmer S, Allan M, Balandin, S. (2015) "We definitely need an audience": experiences of Twitter, Twitter networks and tweet content in adults with severe communication disabilities who use augmentative and alternative communication (AAC). Disability and Rehabilitation, 37,1531-1542.
4. QSR International. (2012). NCapture (Version 1.0.72.0). Doncaster, Victoria: QSR International.
5. Bruns A, Moe H. Structural layers of communication on Twitter. In: Weller K, Bruns A, Burgess Mahrt M, Puschmann C, eds. Twitter and society. New York: Peter Lang; 2014:15-28.
6. Dann S. Benchmarking microblog performance: Twitter Content Classification Framework in Burkhalter. In: Janée N, Wood NT, eds. Maximizing commerce and marketing strategies through micro blogging. Hershey (PA): IGI Global; 2015. pp 318-337.
7. QSR International. (2012). NVivo (Version 10.0.138.0). Doncaster, Victoria: QSR International
8. The Gephi Consortium. (2012). Gephi (Version 0.8.1). Paris: The Gephi Consortium.
9. Fruchterman, T. M. J., & Reingold, E. M. (1991). Graph drawing by force-directed placement. Software: Practice and Experience, 21(11), 1129-1164. doi:10.1002/spe.4380211102.
10. Palmer, S. (2013), Characterisation of the use of Twitter by Australian universities, Journal of Higher Education Policy and Management, v35, n4, pp. 333-344.
11. Higuchi, K. (2014). KH Coder (Version 2.00beta.32). Japan: Koichi Higuchi.
12. Namey, E., Guest, G., Thairu, L., & Johnson, L. (2007). Data reduction techniques for large qualitative data sets. In G. Guest & K. M. MacQueen (Eds.), Handbook for team-based qualitative research (pp. 137-162). Plymouth, UK: Altamira Press.
13. Hu, X., & Liu, H. (2012). Text Analytics in Social Media. In C. C. Aggarwal & C. Zhai (Eds.), Mining Text Data (pp. 385-414): Springer US.