Determinants of Voluntary Organizations’ Attention on Facebook: The Case of Norwegian Voluntary Organizations

Enjolras, Bernard

doi:10.1177/08997640221129551

Cited by 5 publications

(1 citation statement)

References 39 publications

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“…It has long been acknowledged that social media plays a significant role in facilitating stakeholder engagement between nonprofits and community members [ 1 - 3 ]. Human service nonprofits have recognized the potential of social media in securing donations; recruiting volunteers [ 4 - 7 ]; enhancing trust, accountability, and awareness [ 8 ]; and fostering partnerships [ 9 ].…”

Section: Introductionmentioning

confidence: 99%

A Typology of Social Media Use by Human Service Nonprofits: Mixed Methods Study

Xue,

Shier,

Chen

et al. 2024

J Med Internet Res

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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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Section: Introductionmentioning

confidence: 99%

A Typology of Social Media Use by Human Service Nonprofits: Mixed Methods Study

Xue,

Shier,

Chen

et al. 2024

J Med Internet Res

View full text Add to dashboard Cite

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Message Content and Diversity as an Effective Nonprofit Fundraising Strategy on Social Media

Bhati,

McDonnell

2024

Nonprofit and Voluntary Sector Quarterly

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This article explores the relationship between solicitation messages posted by nonprofit organizations on their Facebook profile and attracting donations during online fundraising events. Recent studies suggest that certain types of messages are more effective at spurring donors to give, but the evidence base is founded mainly on experimental designs. We use observational data for 752 nonprofits that participated in one or both of the Omaha Gives fundraising events in 2015 and 2020. Using the total amount of money donated to each organization as our outcome, we find nonprofits that post more diverse solicitation messages raise more money during online fundraising events. Consistent with previous studies, social media network size and activity (likes, posts, and shares) are once again important factors in explaining fundraising success. Our results provide deeper insights into the nuances of social media strategies for attracting donors and raising funds.

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A Typology of Social Media Use by Human Service Nonprofits: Mixed Methods Study (Preprint)

Xue,

Shier,

Chen

et al. 2023

Preprint

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BACKGROUND Current research has shown that nonprofit organizations, generally, are increasingly using social media to enhance their communication strategies with the wider population. Research on social media use within human service nonprofits specifically has identified some hesitancy to use social media education or useful tools to focus on social media use, and there is limited scope among organizational personnel in applying its usefulness beyond promoting one’s organization and its services. There is a 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 aims to leverage the potential of Twitter as a tool for examining the online communication of a sample of nonprofit sexual assault centers. To achieve this, we developed a supervised machine learning model to automatically classify tweets posted by Canadian sexual assault centers based on their organizational outcomes and the sentiment expressed in the tweets. METHODS Employing a mixed-methods approach that combines machine learning and qualitative analysis, we manually coded 10,809 tweets from 133 sexual assault centers in Canada, spanning the period from March 2009 to March 2023. This analysis led to the identification of the following thematic categories: (1) Community Engagement, (2) Organization Administration, (3) Public Awareness, (4) Political Advocacy, (5) Support for Others, (6) Partnerships, and (7) Appreciation. These manually labeled tweets were used as the training dataset 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 utilization 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. Additionally, sentiment analysis was conducted to reveal the emotions conveyed in the tweets. RESULTS Manual annotation of 10,809 tweets identified seven thematic categories, with Organization Administration being the most frequent and Political Advocacy and Partnerships being 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, while joy was associated with Partnership and Appreciation tweets. Topic modeling identified distinct themes within each category, providing valuable insights into the prevalent discussions surrounding sexual assault and related issues. CONCLUSIONS This research contributes an original theoretical model that sheds light on how human service nonprofits utilize Twitter to achieve their organizational outcomes. The study significantly advances our comprehension of Twitter use by human service nonprofits, presenting a comprehensive typology that captures the diverse communication objectives of these organizations. This study provides valuable insights into the content and prevalent themes in nonprofit tweets. This research serves as a foundation for further investigations into the broader applications of social media use within the context of human service nonprofits.

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Determinants of Voluntary Organizations’ Attention on Facebook: The Case of Norwegian Voluntary Organizations

Cited by 5 publications

References 39 publications

A Typology of Social Media Use by Human Service Nonprofits: Mixed Methods Study

A Typology of Social Media Use by Human Service Nonprofits: Mixed Methods Study

Message Content and Diversity as an Effective Nonprofit Fundraising Strategy on Social Media

A Typology of Social Media Use by Human Service Nonprofits: Mixed Methods Study (Preprint)

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