Signitrend: scalable detection of emerging topics in textual streams by hashed significance thresholds

E Schubert, M Weiler, HP Kriegel - Proceedings of the 20th ACM …, 2014 - dl.acm.org
Social media such as Twitter or weblogs are a popular source for live textual data. Much of
this popularity is due to the fast rate at which this data arrives, and there are a number of …

Topicsketch: Real-time bursty topic detection from twitter

W Xie, F Zhu, J Jiang, EP Lim… - IEEE Transactions on …, 2016 - ieeexplore.ieee.org
Twitter has become one of the largest microblogging platforms for users around the world to
share anything happening around them with friends and beyond. A bursty topic in Twitter is …

[HTML][HTML] Recent trends and hotspots in knee arthroplasty: A bibliometric analysis and visualization study of the last five-year publications

M Poursalehian, MH Ebrahimzadeh… - Archives of Bone and …, 2023 - ncbi.nlm.nih.gov
Objectives: Bibliometric analysis is one of the most prevalent methods for analyzing and
predicting the research trends of particular subjects. Through a bibliometric analysis, this …

Destructive leadership in organizational research: a bibliometric approach

M Scheffler, J Brunzel - Scientometrics, 2020 - Springer
The dark side leadership literature remains a highly relevant yet fragmented and ambiguous
literature stream. Therefore, we conduct a bibliometric analysis using co-citation and …

Detecting bursts in sentiment-aware topics from social media

K Xu, G Qi, J Huang, T Wu, X Fu - Knowledge-Based Systems, 2018 - Elsevier
Nowadays plenty of user-generated posts, eg, sina weibos, are published on the social
media. The posts contain the public's sentiments (ie, positive or negative) towards various …

DISCOVERING EMERGING THREATS IN THE HACKER COMMUNITY: A NONPARAMETRIC EMERGING TOPIC DETECTION FRAMEWORK.

W Li, H Chen - MIS Quarterly, 2022 - search.ebscohost.com
The prevalence and rapid growth of cybercrime are largely attributed to hacker communities
on the dark web, where cybercriminals extensively exchange hacking resources, share …

Detecting bursty terms in computer science research

E Tattershall, G Nenadic, RD Stevens - Scientometrics, 2020 - Springer
Research topics rise and fall in popularity over time, some more swiftly than others. The
fastest rising topics are typically called bursts; for example “deep learning”,“internet of …

Detecting trending terms in cybersecurity forum discussions

J Hughes, S Aycock, A Caines, P Buttery, A Hutchings - 2020 - repository.cam.ac.uk
We present a lightweight method for identifying currently trending terms in relation to a
known prior of terms, using a weighted log-odds ratio with an informative prior. We apply this …

Emerging topic detection from microblog streams based on emerging pattern mining

M Peng, S Ouyang, J Zhu, J Huang… - 2018 IEEE 22nd …, 2018 - ieeexplore.ieee.org
Emerging topic detection from microblogs has developed into an attractive task because
events usually break on social channels. However, due to the features of high noise, short …

[PDF][PDF] Time series topic modeling and bursty topic detection of correlated news and twitter

D Koike, Y Takahashi, T Utsuro… - Proceedings of the …, 2013 - aclanthology.org
News and twitter are sometimes closely correlated, while sometimes each of them has quite
independent flow of information, due to the difference of the concerns of their information …