Real-time event detection in social media streams through semantic analysis of noisy terms

T Kolajo, O Daramola, AA Adebiyi - Journal of Big Data, 2022 - Springer
Interactions via social media platforms have made it possible for anyone, irrespective of
physical location, to gain access to quick information on events taking place all over the …

A comprehensive study on social network mental disorders detection via online social media mining

HH Shuai, CY Shen, DN Yang, YFC Lan… - … on Knowledge and …, 2017 - ieeexplore.ieee.org
The explosive growth in popularity of social networking leads to the problematic usage. An
increasing number of social network mental disorders (SNMDs), such as Cyber-Relationship …

Expected tensor decomposition with stochastic gradient descent

T Maehara, K Hayashi, K Kawarabayashi - Proceedings of the AAAI …, 2016 - ojs.aaai.org
In this study, we investigate expected CP decomposition—a special case of CP
decomposition in which a tensor to be decomposed is given as the sum or average of tensor …

Label embedding using hierarchical structure of labels for twitter classification

T Miyazaki, K Makino, Y Takei… - Proceedings of the …, 2019 - aclanthology.org
Twitter is used for various applications such as disaster monitoring and news material
gathering. In these applications, each Tweet is classified into pre-defined classes. These …

Detecting hashtag hijacking from twitter

C VanDam, PN Tan - Proceedings of the 8th ACM Conference on Web …, 2016 - dl.acm.org
Twitter hashtags are typically used to categorize a tweet, to monitor ongoing conversations,
and to facilitate accurate retrieval of posts. Hashtag hijacking occurs when a group of users …

Early detection method for emerging topics based on dynamic bayesian networks in micro-blogging networks

Q Dang, F Gao, Y Zhou - Expert Systems with Applications, 2016 - Elsevier
Micro-blogging networks have become the most influential online social networks in recent
years, more and more people are used to obtain and diffuse information in them. Detecting …

Twitter geolocation using knowledge-based methods

T Miyazaki, A Rahimi, T Cohn… - Proceedings of the 2018 …, 2018 - aclanthology.org
Automatic geolocation of microblog posts from their text content is particularly difficult
because many location-indicative terms are rare terms, notably entity names such as …

The Drift of# MyBodyMyChoice Discourse on Twitter

C Menghini, J Uhr, S Haddadan… - Proceedings of the 14th …, 2022 - dl.acm.org
# MyBodyMyChoice is a well-known hashtag originally created to advocate for women's
rights, often used in discourse about abortion and bodily autonomy. The Covid-19 outbreak …

Time series link prediction using nmf

F Mutinda, A Nakashima, K Takeuchi… - Journal of Information …, 2019 - jstage.jst.go.jp
Data in many fields such as e-commerce, social networks, and web data can be modeled as
bipartite graphs, where a node represents a person and/or an object and a link represents …

Character-based neural embeddings for tweet clustering

S Vakulenko, L Nixon, M Lupu - arXiv preprint arXiv:1703.05123, 2017 - arxiv.org
In this paper we show how the performance of tweet clustering can be improved by
leveraging character-based neural networks. The proposed approach overcomes the …