Browsing by Subject "Crisis"

Now showing 1 - 3 of 3
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    A Typology of Social Media Use by Human Service Nonprofits: Mixed Methods Study
    (JMIR, 2024-05-08) Xue, Jia; Shier, Michael L.; Chen, Junxiang; Wang, Yirun; Zheng, Chengda; Chen, Chen; Biostatistics and Health Data Science, Richard M. Fairbanks School of Public Health
    Background: Nonprofit organizations are increasingly using social media to improve their communication strategies with the broader population. However, within the domain of human service nonprofits, there is hesitancy to fully use social media tools, and there is limited scope among organizational personnel in applying their potential beyond self-promotion and service advertisement. There is a pressing need for greater conceptual clarity to support education and training on the varied reasons for using social media to increase organizational outcomes. Objective: This study leverages the potential of Twitter (subsequently rebranded as X [X Corp]) to examine the online communication content within a sample (n=133) of nonprofit sexual assault (SA) centers in Canada. To achieve this, we developed a typology using a qualitative and supervised machine learning model for the automatic classification of tweets posted by these centers. Methods: Using a mixed methods approach that combines machine learning and qualitative analysis, we manually coded 10,809 tweets from 133 SA centers in Canada, spanning the period from March 2009 to March 2023. These manually labeled tweets were used as the training data set for the supervised machine learning process, which allowed us to classify 286,551 organizational tweets. The classification model based on supervised machine learning yielded satisfactory results, prompting the use of unsupervised machine learning to classify the topics within each thematic category and identify latent topics. The qualitative thematic analysis, in combination with topic modeling, provided a contextual understanding of each theme. Sentiment analysis was conducted to reveal the emotions conveyed in the tweets. We conducted validation of the model with 2 independent data sets. Results: Manual annotation of 10,809 tweets identified seven thematic categories: (1) community engagement, (2) organization administration, (3) public awareness, (4) political advocacy, (5) support for others, (6) partnerships, and (7) appreciation. Organization administration was the most frequent segment, and political advocacy and partnerships were the smallest segments. The supervised machine learning model achieved an accuracy of 63.4% in classifying tweets. The sentiment analysis revealed a prevalence of neutral sentiment across all categories. The emotion analysis indicated that fear was predominant, whereas joy was associated with the partnership and appreciation tweets. Topic modeling identified distinct themes within each category, providing valuable insights into the prevalent discussions surrounding SA and related issues. Conclusions: This research contributes an original theoretical model that sheds light on how human service nonprofits use social media to achieve their online organizational communication objectives across 7 thematic categories. The study advances our comprehension of social media use by nonprofits, presenting a comprehensive typology that captures the diverse communication objectives and contents of these organizations, which provide content to expand training and education for nonprofit leaders to connect and engage with the public, policy experts, other organizations, and potential service users.
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    Giving Following a Crisis: An Historical Analysis
    (1/21/2010) Brown, Melissa S.; Rooney, Patrick M.
    While conventional wisdom in fundraising maintains that donors of all types give in response to need, analysis of contributions from 1939 to 1999, including years of 17 national crises ranging from war, natural disaster, political crisis, and terrorism, shows that economic variables are strongly associated with giving, whereas crisis is seldom a significant factor. Crisis seems to matter in bivariate (giving/crisis) analysis, but not after controlling for economic changes in multivariate analyses. Results are very robust to type of crisis, time period, sources of giving and specification of model.
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    How Public Libraries Respond to Crises Involving Patrons Experiencing Homelessness: Multiple Perspectives of the Role of the Public Library Social Worker
    (2023-05) Provence, Mary Anita; Starnino, Vincent; Adamek, Margaret; Copeland, Andrea; Kyere, Eric; Wahler, Elizabeth
    Due to a shortage of affordable housing, gaps in social welfare infrastructure, and the criminalization of homelessness, public libraries find themselves providing daytime shelter to patrons experiencing homelessness. Their needs and crises have created demands on staff and security that exceed their training and role. Sometimes police are involved, exposing patrons to possible arrest. To fill this knowledge and service gap, libraries have begun hiring social workers. Early research on the broad role of social workers suggests they are changing how libraries respond to crises with patrons experiencing homelessness in four keyways: by providing an option to calling 911; influencing code of conduct implementation, serving patrons, and equipping staff. However, no study has given an in-depth explanation of how social workers are changing libraries’ responses to crises with patrons experiencing homelessness. The purpose of this study is to explain how the role of the social worker influences how libraries respond when patrons experiencing homelessness are in crises. Considered through lenses of role theory, social cognitive theory, and the humanization framework, this embedded multiple-case study of three U.S. urban libraries collected 91 surveys and conducted 46 Zoom interviews. It includes the perspectives of 107 participants across six roles: patrons experiencing homelessness, social workers, front-facing staff, security, location managers, and CEOs. The social workers’ influence was perceived to reduce behavior incidents, exclusions, and arrests around three themes: (1) being an option, with subthemes of in-house referrals and de-escalation; (2) running interference, with subthemes of low barrier access and barrier-busting services; and (3) buffering, with subthemes of equipping, influencing code of conduct implementation, and advocating and being present during security and police interactions. Three models of library social work and their impact on the social worker’s role of de-escalation were identified and described: The Sign Up and Summon Model, the Outreach and Summon Model, and the Social Work Center Model. In addition, a commingled rival was found: the impact of the Black Lives Matter movement. The implications of the findings include recommendations for structuring library social work practice to reduce exclusions and arrests of patrons experiencing homelessness.