Machine learning algorithms for social media analysis: A survey

TK Balaji, CSR Annavarapu, A Bablani - Computer Science Review, 2021 - Elsevier
Social Media (SM) are the most widespread and rapid data generation applications on the
Internet increase the study of these data. However, the efficient processing of such massive …

Directions in abusive language training data, a systematic review: Garbage in, garbage out

B Vidgen, L Derczynski - Plos one, 2020 - journals.plos.org
Data-driven and machine learning based approaches for detecting, categorising and
measuring abusive content such as hate speech and harassment have gained traction due …

Autoregressive entity retrieval

N De Cao, G Izacard, S Riedel, F Petroni - ar** machines with comprehensive knowledge of the world's entities and their
relationships has been a longstanding goal of AI. Over the last decade, large-scale …

[KSIĄŻKA][B] Feature engineering for machine learning and data analytics

G Dong, H Liu - 2018 - books.google.com
Feature engineering plays a vital role in big data analytics. Machine learning and data
mining algorithms cannot work without data. Little can be achieved if there are few features …

Improving multimodal named entity recognition via entity span detection with unified multimodal transformer

J Yu, J Jiang, L Yang, R **a - 2020 - ink.library.smu.edu.sg
In this paper, we study Multimodal Named Entity Recognition (MNER) for social media posts.
Existing approaches for MNER mainly suffer from two drawbacks:(1) despite generating …