Higher Education Institutions' Attractiveness

Autor: Olga Yugay, Aziz Nasridinov, Vasiliy Kuznetsov, Dilnoza Muslimova
Rok vydání: 2015
Předmět:
Zdroj: Proceedings of the 2015 International Conference on Big Data Applications and Services.
DOI: 10.1145/2837060.2837099
Popis: The aim of this paper is to present the ongoing research on the use of social media in higher education. The paper introduces a method of evaluating and predicting potential number of applicants by means of social media in order to optimize related costs. We propose to assess university attractiveness for applicants by analyzing data collected through social networks (e.g. Twitter) to allow a timely adjustment of marketing efforts. Such analysis will allow early prediction of the number of potential applicants as a result will accommodate timely adjustment of the marketing and administrative efforts for potential student intake. Moreover, we analyze "positive", "negative" and "neutral" tweets in Twitter and their effect on the prediction. Our results suggest that the number of tweets is positively correlated with the number of applications. However, the strength of correlation is not stable across the sampled months, depicting the strongest degree to be in August. Interestingly, greater number of positive tweets appears to be associated with lower students' application figures and vice versa. Additionally the paper outlines major limitations associated with data collection and analysis.
Databáze: OpenAIRE