Predicting donation behavior: Acquisition modeling in the nonprofit sector using Facebook data

Schetgen, Lisa; Bogaert, Marcus; Poel, Dirk Van den

doi:10.1016/j.dss.2020.113446

Cited by 17 publications

(8 citation statements)

References 53 publications

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“…3 , with the green training period for building the model, orange validation period for tuning the hyperparameters (and final training) and red testing period for evaluating final performance. A single train-validation split is used to optimize the hyperparameters as is common in predictive modelling studies (Schetgen et al, 2021 ). Hence, the validation period is only used for hyperparameter tuning and the combined training and validation period is eventually used for fitting the final model.…”

Section: Methodsmentioning

confidence: 99%

Predicting the next Pogačar: a data analytical approach to detect young professional cycling talents

2022

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The importance of young athletes in the field of professional cycling has sky-rocketed during the past years. Nevertheless, the early talent identification of these riders largely remains a subjective assessment. Therefore, an analytical system which automatically detects talented riders based on their freely available youth results should be installed. However, such a system cannot be copied directly from related fields, as large distinctions are observed between cycling and other sports. The aim of this paper is to develop such a data analytical system, which leverages the unique features of each race and thereby focusses on feature engineering, data quality, and visualization. To facilitate the deployment of prediction algorithms in situations without complete cases, we propose an adaptation to the k-nearest neighbours imputation algorithm which uses expert knowledge. Overall, our proposed method correlates strongly with eventual rider performance and can aid scouts in targeting young talents. On top of that, we introduce several model interpretation tools to give insight into which current starting professional riders are expected to perform well and why.

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Section: Methodsmentioning

confidence: 99%

Predicting the next Pogačar: a data analytical approach to detect young professional cycling talents

2022

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“…There are many factors that affect donations to an organization apart from engagement of a social media platform including sociodemographic factors, attitude and involvement in charity or a nonprofit organization 25,26 . Specifically, for disaster situations (i.e.…”

Section: Discussionmentioning

confidence: 99%

The Correlation of Social Media Activity and Engagement of a Health NGO with the Outcome of Fundraising Efforts During the COVID-19 Pandemic

Rashid

Idris

Zulkiflee³

et al. 2021

Bangladesh J Med Sci

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Objective: The COVID-19 pandemic saw the involvement of many health non-governmental organisations (NGO) with volunteering work to help reduce the burden of healthcare workers (HCW). IMAM Response and Relief Team (IMARET) is one which is a chapter under the Islamic Medical Association of Malaysia (IMAM); which is also under the umbrella of the Federations of Islamic Medical Associations (FIMA). IMARET often aids HCWs during natural and manmade disasters to help reduce their burden during challenging times by providing manpower, equipment, and logistical assistance. IMARET utilizes social media (SM) for spreading information on their activities to the public, like the COVID-19 fundraising efforts. The objective of this research is to determine the correlation between their Facebook activities and fundraising outcome. Materials and Methods: This is a cross sectional study of Facebook posts and its engagement with Billplz, an online payment platform focused during the initial COVID-19 fundraising effort. Results and Discussion: During the study period, we report 346 Facebook posts with a median (IQR) of 8.00 (6.00,9.00) posts per day. As many as 4,823 donations, median (IQR) at RM34.50(18.75,86.00) was received per day. RM3425,50 (USD 830.52) (1369.00, 8376.25) was collected per day. ‘Organic Likes’ correlated significantly with the number of donations (r=0.419,p=0.006) and amount received (r=0.355,p=0.021). Both ‘Post Reach’ and ‘Shares’ significantly correlated with the number of donations (r=0.405,p=0.008)(r=0.515,p<0.01)and amount received (r=0.373,p=0.015) (r=0.453,p=0.003) respectively. Conclusion: The number of likes, reach and shares significantly correlated with the number and amount of donations received during the initial phase of the IMARET COVID-19 fundraising effort Bangladesh Journal of Medical Science Vol.20(5) 2021 p.148-154

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“…Though social media started as a medium to connect individuals, it has quickly evolved into an all-encompassing medium of communication (Chen et al, 2015;Schetgen et al, 2020). At the individual level, social media has been used to connect and discuss both mundane and socially relevant topics simultaneously (Kushwaha et al, 2020a).…”

Section: Firm Communication On Social Mediamentioning

confidence: 99%

Social Media Sustainability Communication: An Analysis of Firm Behaviour and Stakeholder Responses

Jha

Verma

2022

Inf Syst Front

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Social media communication, and its impact on individuals and firms, is becoming increasingly important in today’s age. Firms are utilizing social media channels for communicating their sustainability-related initiatives. The role of social media as a mode for sustainability-related communication by firms has not been widely analyzed in the extant information systems literature. Given the increasingly important role of social media for information diffusion as well as increasing awareness for sustainability practices, this is a critical area of research. In this paper, we use an analytic model to theorize, coupled with empirical analysis to test the impact of firms’ sustainability practices. We have validated our proposed hypotheses using an empirical model based on panel data of firms’ sustainability performance and their Twitter communication over a 3-year period. Through our unique mixed-method study, we add additional methodological rigour to extant social media-based research in the information systems domain. Our research has significant theoretical and managerial significance as we identify how firms utilize social media for sustainability-related communication and its corresponding impact on customer response. Our research provides actionable insights for policymakers, firms as well as investors and consumers on understanding and managing sustainability-related communications on social media.

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Predicting donation behavior: Acquisition modeling in the nonprofit sector using Facebook data

Cited by 17 publications

References 53 publications

Predicting the next Pogačar: a data analytical approach to detect young professional cycling talents

Predicting the next Pogačar: a data analytical approach to detect young professional cycling talents

The Correlation of Social Media Activity and Engagement of a Health NGO with the Outcome of Fundraising Efforts During the COVID-19 Pandemic

Social Media Sustainability Communication: An Analysis of Firm Behaviour and Stakeholder Responses

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