A poster on strategies and uses of Twitter for cancer communication presented at the 2016 Annual Meeting of the Medical Library Association. Second place award for Research Poster at the conference.

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www.PosterPresentations.com
Engaging Diverse Communities in Cancer Conversations
Through Creation of Structure & Metadata Within Twitter
Patricia F. Anderson1
<pfa@umich.edu>, Matthew S. Katz2
, Audun Utengen3
, Michael A. Thompson4
, Michael Fisch5
,
Claire Johnston6
, Deanna J. Attai7
, Lee Aase8
, Robert S. Miller6
, Thomas Lee2
, Don S. Dizon9
1) University of Michigan, Ann Arbor, MI; 2) Lowell General Hospital, Lowell, MA; 3) Symplur, LLC, Los Angeles, CA; 4) Aurora Research Institute, Aurora Health Care, Milwaukee, WI; 5) AIM Specialty Health, Chicago, IL;
6) ASCO, Alexandria, VA; 7) David Geffen School of Medicine at University of California, Los Angeles, Los Angeles, CA; 8) Mayo Clinic, Rochester, MN; 9) Massachusetts General Hospital, Boston, MA
Objectives
Intending to develop an online space engaging to both clinicians and patients, we
created a cancer tag ontology for Twitter. The goal was to foster boundary-spanning
between diverse communities, to build off the successes and best practices of
existing Twitter cancer hashtag communities, and to encourage self-managed
communities for information quality, in the context of appropriate metadata practices.
Methods
Metadata Structures & Other Constraints on Tag Development
Tag ontologies designed for social media use face constraints based on the
technologies and communities of use which do not apply to more formally constructed
ontologies. Traditional ontologies clarify conceptual relationships, and facilitate
knowledge-sharing, coding, interrogation of the data, and analytic uses based on the
structured terminology. Social media tags have historically avoided the formalism of an
ontological structure, but have evolved certain common practices through communities
of use within the specific platform(s). Those common practices make it possible to
predict a likely tag for a novel concept as well as to discover existing tags and the
communities which use them. A well-designed tag ontology attempts to maximise the
benefits of both standard ontology design practices as well as common practices in the
targeted social media communities. At the same time, it attempts to minimise the
potential problems inherent in applying structure to what originated as an unstructured
user-driven folksonomic type of naming activity. These are some of the compromises
and negotiated prioritization we developed as criteria for tag ontology development.
● Adoption of broad and widely adopted best practices for tag creation driven by
technology limits such as limited character conventions in tweets.
● Incorporation of pre-existing tags and tag conventions created by the target
community (i.e. #bcsm, #btsm, #lcsm).
● Adoption of a standard tag format or structure convention for new tags (i.e. #—sm).
● Balance ease of identification & memorization with internal community jargon, which
helps to minimize spam initially.
● Capitalization standardization to encourage accessibility best practices through use
of CamelCase (i.e. #gyncsm vs. #GynCSM)
● Identify top level concepts and conceptual structures. Attempt to group tags on
related concepts under common stem. This facilitates identification of conceptual
relationships, portability, and facilitates data analysis derived from the tagged
content. Note, this is an ideal, and often not possible. Example: #GynCSM could
incorporate ovarian cancer. Ideally, for best practices with stemming, this would
take a format such as #GynCSMocsm or #GynCSMovca. For real world practice,
the ovarian cancer community is already actively using #OvCa and #OCSM.
Figure 1: Tweets & Participants by CTO Hashtag
Figure 2a: Stakeholder Mix Figure 2b: Tweet Activity by Type
Figure 3: Twitter Use by Stakeholder Type & Hashtag
Table 1: Hashtags in the Cancer Tag Ontology
Figure 4: Twitter Activity: a) Quarterly b) Monthly
Results
Conclusions
More Information
● For the entire study period, there were a total of 531,765 tweets by 77,454 users
[Figure 1]
● The two user-generated tags #bcsm and #btsm had the longest use and most
activity with 249,312 and 110,465 tweets, respectively
● The most active new hashtags were those with organized Twitter-based chats:
#ayacsm; #gyncsm; #lcsm; #mmsm; and #pancsm. These seven accounted for
93% of new hashtag use.
● In the cohort, 11% were patients, 20% doctors, 3% non-doctor healthcare
professional, 32% individual, 30% healthcare organization, 1% other
organization, and 3% spam. [Figure 2a]
● The most active top users were patients with a median of 46 tweets. [Figure 2b]
● Differences in user mix for the tags with chats are highlighted in Figure 3.
● Activity using the CTO increased from 13,778 tweets in Q3 2011 to 75,960
tweets in Q3 2014 [Figure 4a]
● For the 23 structured tags, quarterly use increased from 18,098 tweets in Q3
2013 to 39,761 tweets in Q3 2014 [Figure 4b]
● All NIH Comprehensive Cancer Centers use the tag ontology.
● Wide adoption has spawned five new independent tag ontologies, with more in
development: cardiology, oncology, pathology, radiology, urology.
● Typical hashtag adoption patterns have shown a reluctance to adopt prescribed
hashtags outside of formal events.
● The success of the tag ontology shows the desire for engagement and
partnership among the target communities.
● We have demonstrated the feasibility and growth of organized, cancer-specific
hashtags on Twitter used by a variety of stakeholders in cancer care.
● Use of the CTO indicates potential value of online interaction.
● Further study is needed to determine whether the CTO has any impact on
access, outcomes, information quality, as a model for other areas of medicine, or
as a resource for future research.
Based upon two de novo hashtags, #bcsm (breast cancer social media) and #btsm
(brain tumor social media), an organized system of hashtags was designed in July
2013 for online use. This system is now known as the cancer tag ontology (CTO).
Metadata criteria applied included factors such as length, standard formatting,
adherence to alphabetical sorting for related subtopics, and similar principles. All
tweets were archived in the Symplur Healthcare Hashtag Project for later analysis.
We conducted a retrospective study of 25 hashtags used on Twitter April 2011 –
September 2014 using data from Symplur, LLC. We classified up to 100 most active
users of each hashtag as follows: patient; doctor; non-doctor health care professional
(HCP); individual NOS (I); healthcare organization (HCO), other organization (OO); or
spam. Tweet activity was analyzed quarterly for all tags.
Background
● A majority of patients and health care professionals are now online
● Many cancer patients seek accurate health information online, which isn’t always
easy to access or identify
● Robust, active communities emerged on Twitter using hashtags for breast cancer
social media (#bcsm) and brain tumor social media (#btsm) in 2011 and 2012,
respectively
● Patient advocates started #bcsm and #btsm for advocacy and support, both
including doctors with #bcsm involving one author (DJA) as a collaborator
● A disease-specific ontology [structured tags without pre-existing use] was developed
by two authors (MSK and PFA) and shared online in July 2013
● After public commentary and discussion for community engagement, a finalized
version was posted online in November 2013 on Symplur.com
● Initially described as a folksonomy (user-generated system), we defined the hashtag
sets as an ontology, a structured system designed a priori
● Our hypothesis is that cancer-specific hashtags are a promising way to facilitate
access to accurate health information and positive interactions
● Our aim was to retrospectively evaluate Twitter use of the Cancer Tag Ontology
(CTO) and the types of users putting these hashtags into tweets
● Symplur: Healthcare Hashtags: Ontologies: <http://www.symplur.com/healthcare-hashtags/ontology/>
● Katz MS, Utengen A, Anderson PF, Thompson MA, Fisch M, Johnston C, Attai DJ, Aase L, Miller RS, Lee T,
Dizon DS. Disease specific hashtags for communication about cancer care. ASCO Annual Meeting 2015. <http:
//www.slideshare.net/subatomicdoc/disease-specific-hashtags-for-communication-about-cancer-care-48866106>
● Katz MS, Utengen A, Anderson PF, Thompson MA, Attai DJ, Johnston C, Dizon DS. Disease-Specific Hashtags
for Online Communication About Cancer Care. JAMA Oncol. 2016 Mar 1;2(3):392-4. doi: 10.1001/jamaoncol.
2015.3960.
● Attai DJ1, Sedrak MS2, Katz MS3, Thompson MA4, Anderson PF5, Kesselheim JC6, Fisch MJ7, Graham DL8,
Utengen A9, Johnston C10, Miller RS10, Dizon DS11; Collaboration for Outcomes on Social Media in Oncology
(COSMO). Social media in cancer care: highlights, challenges & opportunities. Future Oncol. 2016 Mar 30.
#adcsm Adrenal Cancer #lcsm Lung Cancer
#ancsm Anal Cancer #leusm Leukemia
#ayacsm Adolescent & Young Adult
Cancer
#lymsm Lymphoma
#bcsm Breast Cancer #melsm Melanoma
#blcsm Bladder Cancer #mmsm Multiple Myeloma
#btsm Brain Tumors #pancsm Pancreatic Cancer
#crcsm Colorectal Cancer #pcsm Prostate Cancer
#esocsm Esophageal Cancer #pedcsm Pediatric Cancer
#gyncsm Gynecologic Cancers #scmsm Sarcoma
#hncsm Head & Neck Cancers #stcsm Stomach Cancer
#hpbcsm Hepatobiliary Cancers #thmcsm Thymoma & Thymic
Carcinoma
#kcsm Kidney Cancer #thycsm Thyroid Cancer
#tscsm Testicular Cancer
Table 2: Classification of the Most Active Users of the Hashtags
Patient
(P)
Doctor
(D)
Healthcare
Professional,
Other (HCP)
Individual,
Other (I)
Healthcare
Organization
(HCO)
Organization,
Other (OO)
Spam
(S)
4a: Quarterly Twitter Activity of the CTO,
2011-2014
4a: Monthly Twitter Activity of the
Structured Tags, 2013-2014