Abstract: On Twitter, hashtags are used to summarize topics of the tweet content and to help search tweets. However, hashtags are created in a free style and thus heterogeneous, increasing difficulty of their usage. Therefore, it is important to evaluate that if they really represent the content they are attached with? In this work, we perform detailed experiments to find answer for this question. In addition to this, we compare different semantic relatedness measures to find this similarity between hashtags and tweets. Experiments are performed using ten different measures and Adapted Lesk is found to be the best.

Muhammad Asif, Malik Muhammad Saad Missen, Nadeem Akhtar, Hina Asmat, Mujtaba Husnain and Muhammad Asghar, “Hashtag the Tweets: Experimental Evaluation of Semantic Relatedness Measures” International Journal of Advanced Computer Science and Applications(IJACSA), 7(6), 2016. http://dx.doi.org/10.14569/IJACSA.2016.070662

@article{Asif2016,
title = {Hashtag the Tweets: Experimental Evaluation of Semantic Relatedness Measures},
journal = {International Journal of Advanced Computer Science and Applications}
doi = {10.14569/IJACSA.2016.070662},
url = {http://dx.doi.org/10.14569/IJACSA.2016.070662},
year = {2016},
publisher = {The Science and Information Organization},
volume = {7},
number = {6},
author = {Muhammad Asif and Malik Muhammad Saad Missen and Nadeem Akhtar and Hina Asmat and Mujtaba Husnain and Muhammad Asghar},
}