| Title |
Socialinės žiniasklaidos rinkodaros sprendimų tobulinimas panaudojant didžiųjų verslo duomenų analitikos sprendimus / |
| Translation of Title |
Social media marketing decisions improvement through big data analytics decisions. |
| Authors |
Radvilavičius, Edvinas |
| Full Text |
|
| Pages |
83 |
| Keywords [eng] |
social media ; marketing ; social network ; engagement |
| Abstract [eng] |
The aim of Master's final project was to improve social media marketing decisions through big business data analytics. The work revealed the peculiarities of social media marketing and identified an issue requiring optimization – posts that do not get enough engagement from social network users. By identifying the importance of consumer engagement, the aim was to create a model that would predict whether the post would become engaged. This kind of problem was defined as a classification task the most appropriate classification methods were found to solve it - decision tree, random forest, neural networks and logistic regression. By building the classification models, it has been found that the random forest model is the most predictive model for predicting the engagement of a post. After analyzing the literature and research methods and evaluating the accuracy of the model, it can be concluded that social media marketing solutions in the social network „Facebook“ can be improved by using big data analytics solutions. |
| Dissertation Institution |
Kauno technologijos universitetas. |
| Type |
Master thesis |
| Language |
Lithuanian |
| Publication date |
2018 |
