Cancer and Social Media: A Comparison of Traffic about Breast Cancer, Prostate Cancer, and Other Reproductive Cancers on Twitter and Instagram

Abstract

Social media are often heralded as offering cancer campaigns new opportunities to reach the public. However, these campaigns may not be equally successful, depending on the nature of the campaign itself, the type of cancer being addressed, and the social media platform being examined. This study is the first to compare social media activity on Twitter and Instagram across three time periods: #WorldCancerDay in February, the annual month-long campaigns of National Breast Cancer Awareness Month (NBCAM) in October and Movember in November, and during the full year outside of these campaigns. Our results suggest that women's reproductive cancers - especially breast cancer - tend to outperform men's reproductive cancer - especially prostate cancer - across campaigns and social media platforms. Twitter overall generates substantially more activity than Instagram for both cancer campaigns, suggesting Instagram may be an untapped resource. However, the messaging for both campaigns tends to focus on awareness and support rather than on concrete actions and behaviors. We suggest health communication efforts need to focus on effective messaging and building engaged communities for cancer communication across social media platforms.

Content shared on social media for national cancer survivors day 2018

“…However, as described in previous work, [27] we also found that most cancer-related social media posts focus on cancers that predominantly affect women, suggesting that social media does not offer the same appeal as a venue for men's illness narratives. Conceptualized as a space for social support, this observation follows the general trend that men lack the robust social networks often found among women, both virtually and in real life.…”

“…To put our findings in the context of literature on social media and cancer to date, aligned with previous studies, our analysis of posts from National Cancer Survivors Day demonstrates how cancer awareness months promote awareness by the sharing of illness narratives and treatment trajectories on social media. [20,26,27,29].…”

“…In aggregate, these posts may create a window to better understand the meaning of survivorship for cancer patients as a whole. [25][26][27] However, just because social media platforms aren't mediated in the same way as traditional venues (e.g. support groups) or research activities (e.g.…”

Strategies for Effective Health Communication during the Coronavirus Pandemic and Future Emerging Infectious Disease Events

“…Social media analytics may also reveal which health issues and which at‐risk populations are not participating in online conversations and are therefore missing out on opportunities for health education. For example, data analyses might show gender gaps in which health issues receive online attention (Vraga et al, 2018) or identify when media engagement about a health issue is being displaced by political campaigns (Vraga et al, 2017). Understanding what information about a public health issue is missing on social media enables organizations to update their communication strategies.…”

Computational Social Science of Disasters: Opportunities and Challenges

“…Prominent examples of such initiatives include Data.gov in the U.S. and OpenKenya [113] in the Republic of Kenya (see [114] for how such data can be used). The ever-increasing popularity of social media, enabled by Web 2.0 technology, is expanding the sources and volume of social data relevant to our daily lives through applications such as Facebook, Twitter, and Instagram, and these open sources are allowing researchers to explore a vast range of topics, including opinions during elections [115], opinions on public health [116], data on disease outbreaks [117], and studies of the connections between people and places [118,119]. The relevance and management of open-source data has become more important than ever, and they are well-positioned to support the quantitative study of disasters through the use of new computational methods, such as machine learning, natural language processing, sentiment analysis, and artificial intelligence [120].…”