#Socialworkeducation: A Computational Analysis of Social Work Schools and Programs Using Twitter

Social media can be a valuable tool in social work education to help collaborate with others, promote programs, engage with alumni, or promote interprofessional education. Social media are defined as an array of digital technologies that allow for the creation and exchange of user generated content (Kaplan & Haenlein, 2010; Kanter & Fine, 2010) and include digital platforms such as Facebook, Twitter, YouTube, and Snapchat. As more and more organizations adopt social media to promote their services (Goldkind, 2015; Young, 2017), social work education programs have also utilized social media for a variety of purposes.

The purpose of this study is to examine how social work education programs use Twitter by leveraging the principles of data science. Data science allows for the analysis of big data sets that can be structured or unstructured to develop understanding, extract knowledge, and formulate actionable results (Cariceo, Nair, & Lytton, 2018, p. 1). Specifically, a text and sentiment analysis of 26,000 tweets, collected over a 10-month period, was performed to identify how social work programs use Twitter and what kind of tone, or sentiment, their tweets contain. Utilizing the Lovejoy & Saxton (2012) framework a Sentiment analysis helped to identify tweets as positive, neutral, or negative based on the frequency of words within the tweet by using a lexicon based within the Azure Machine Learning program. This data mining analysis helps to illustrate how programs engage with other Twitter users to promote their respective schools or programs.

The findings suggest that programs tweet primarily to share information about a variety of topics and opportunities, categorized as Information. Programs also tweet calls to action and try to engage with their online community but not at the same level of sharing information, categorized as Action. A smaller sample of the tweets did engage in more of a dialogic connection between users to promote conversation or interaction, categorized as Community. A majority of the tweets have a neutral sentiment with some also being identified as positive or negative. Interestingly, larger programs were able to produce more tweets and engage with a larger audience. Tweets by larger programs often received more likes and retweets than other smaller programs. A possible reason for this could be the number of staff available in larger programs, but more research is needed to have a definitive conclusion.

Social Work programs can play a pivotal role in helping students to become lifelong learners, increase their digital literacies, and model ethical and appropriate technology use through their curriculum and online presence. However, technology in social work education has been adopted sporadically with moderate degrees of success. This study supports this notion by evaluating how social work programs use Twitter for a variety of purposes. Attendees will understand how programs are using Twitter and gain ideas for their own programs and efforts regarding the use of social media. By examining the past usage of Twitter, this presentation will help participants look forward to understand how to use Twitter in more effective ways.