Three gaps in computational text analysis methods for social sciences: A research agenda

C Baden, C Pipal, M Schoonvelde… - Communication …, 2022 - Taylor & Francis
We identify three gaps that limit the utility and obstruct the progress of computational text
analysis methods (CTAM) for social science research. First, we contend that CTAM …

Short text topic modeling techniques, applications, and performance: a survey

J Qiang, Z Qian, Y Li, Y Yuan… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Analyzing short texts infers discriminative and coherent latent topics that is a critical and
fundamental task since many real-world applications require semantic understanding of …

User OCEAN personality model construction method using a BP neural network

X Qin, Z Liu, Y Liu, S Liu, B Yang, L Yin, M Liu… - Electronics, 2022 - mdpi.com
Highlights What are the main findings? First, the combination of the methods of machine
learning with psychological methods to predict the user's OCEAN personality model could …

Topic modeling and sentiment analysis of global climate change tweets

B Dahal, SAP Kumar, Z Li - Social network analysis and mining, 2019 - Springer
Social media websites can be used as a data source for mining public opinion on a variety
of subjects including climate change. Twitter, in particular, allows for the evaluation of public …

Applications of topic models

J Boyd-Graber, Y Hu, D Mimno - Foundations and Trends® in …, 2017 - nowpublishers.com
How can a single person understand what's going on in a collection of millions of
documents? This is an increasingly common problem: sifting through an organization's e …

Topic modeling for short texts with auxiliary word embeddings

C Li, H Wang, Z Zhang, A Sun, Z Ma - Proceedings of the 39th …, 2016 - dl.acm.org
For many applications that require semantic understanding of short texts, inferring
discriminative and coherent latent topics from short texts is a critical and fundamental task …

[BUCH][B] Searchable talk: Hashtags and social media metadiscourse

M Zappavigna - 2018 - books.google.com
Metadata such as the hashtag is an important dimension of social media communication.
Despite its important role in practices such as curating, tagging, and searching content, there …

Big social data analytics in journalism and mass communication: Comparing dictionary-based text analysis and unsupervised topic modeling

L Guo, CJ Vargo, Z Pan, W Ding… - Journalism & Mass …, 2016 - journals.sagepub.com
This article presents an empirical study that investigated and compared two “big data” text
analysis methods: dictionary-based analysis, perhaps the most popular automated analysis …

How sensory language shapes influencer's impact

GL Cascio Rizzo, J Berger, M De Angelis… - Journal of Consumer …, 2023 - academic.oup.com
Influencer marketing has become big business. But while influencers have the potential to
spread marketing messages and drive purchase, some posts get lots of engagement and …

Combining machine-learning topic models and spatiotemporal analysis of social media data for disaster footprint and damage assessment

B Resch, F Usländer, C Havas - Cartography and geographic …, 2018 - Taylor & Francis
Current disaster management procedures to cope with human and economic losses and to
manage a disaster's aftermath suffer from a number of shortcomings like high temporal lags …