A system for extracting and comparing memes in online forums
Item
Title
A system for extracting and comparing memes in online forums
Expert Systems with Applications
Creator
Héctor Beck-Fernandez
David F. Nettleton
Lorena Recalde
Diego Saez-Trumper
Alexis Barahona-Peñaranda
Abstract
From their origins in the sociological field, memes have recently become of interest in the context of `viral' transmission of basic information units (memes) in online social networks. However, much work still needs to be done in terms of metrics and practical data processing issues. In this paper we define a theoretical basis and processing system for extracting and matching memes from free format text. The system facilitates the work of a text analyst in extracting this type of data structures from online text corpuses and n performing empirical experiments in a controlled manner. The general aspects related to the solution are the automatic processing of unstructured text without need for preprocessing (such as labelling and tagging), identification of co-occurences of concepts and corresponding relations, construction of semantic networks and selecting the top memes. The system integrates these processes which are generally separate in other state of the art systems. The proposed system is important because unstructured online text content is growing at a greater rate than other content (e.g. semi-structured, structured) and integrated and automated systems for knowledge extraction from this content will be increasingly important in the future. To illustrate the method and metrics we process several real online discussion forums, extracting the principal concepts and relations, building the memes and then identifying the key memes for each document corpus using a sophisticated matching process. The results show that our method can automatically extract coherent key knowledge from free text, which is corroborated by benchmarking with a set of other text analysis approaches, as well as a user study evaluation.
volume
82
issue
Supplement C
pages
231-251
Date
October 1, 2017
short title
Expert Systems with Applications
Language
EN English
doi
10.1016/j.eswa.2017.04.010
issn
0957-4174