What demographic attributes do our digital footprints reveal? A systematic review

J Hinds, AN Joinson - PloS one, 2018‏ - journals.plos.org
To what extent does our online activity reveal who we are? Recent research has
demonstrated that the digital traces left by individuals as they browse and interact with …

[HTML][HTML] Methods for coding tobacco-related Twitter data: a systematic review

BA Lienemann, JB Unger, TB Cruz, KH Chu - Journal of medical Internet …, 2017‏ - jmir.org
Background As Twitter has grown in popularity to 313 million monthly active users,
researchers have increasingly been using it as a data source for tobacco-related research …

Predictive analysis on Twitter: Techniques and applications

U Kursuncu, M Gaur, U Lokala, K Thirunarayan… - … research challenges and …, 2019‏ - Springer
Predictive analysis of social media data has attracted considerable attention from the
research community as well as the business world because of the essential and actionable …

Are people located in the places they mention in their tweets? a multimodal approach

Z **ao, E Blanco - … of the 29th International Conference on …, 2022‏ - aclanthology.org
This paper introduces the problem of determining whether people are located in the places
they mention in their tweets. In particular, we investigate the role of text and images to solve …

What's in a name?–gender classification of names with character based machine learning models

Y Hu, C Hu, T Tran, T Kasturi, E Joseph… - Data Mining and …, 2021‏ - Springer
Gender information is no longer a mandatory input when registering for an account at many
leading Internet companies. However, prediction of demographic information such as …

Categorizing the non-categorical: the challenges of studying gendered phenomena online

S Shugars, A Quintana-Mathé… - Journal of Computer …, 2024‏ - academic.oup.com
Studies of gendered phenomena online have highlighted important disparities, such as who
is likely to be elevated as an expert or face gender-based harassment. This research …

Feature engineering for social bot detection

O Varol, CA Davis, F Menczer… - Feature engineering for …, 2018‏ - taylorfrancis.com
This chapter presents the most common approaches used in systems for identifying social
bots. It focuses on egocentric analysis methodology due to its advantages with respect to …

A Comparative Analysis of Classic and Deep Learning Models for Inferring Gender and Age of Twitter Users [A Comparative Analysis of Classic and Deep Learning …

Y Liu, L Singh, Z Mneimneh - … of the 2nd International Conference on …, 2021‏ - par.nsf.gov
In order for social scientists to use social media as a source for understanding human
behavior and public opinion, they need to understand the demographic characteristics of the …

Towards open-domain Twitter user profile inference

H Wen, Z **ao, E Hovy… - Findings of the …, 2023‏ - aclanthology.org
Twitter user profile inference utilizes information from Twitter to predict user attributes (eg,
occupation, location), which is controversial because of its usefulness for downstream …

Utilizing External Knowledge to Enhance Location Prediction for Twitter/X Users in Low Resource Settings

Y Liu, L Singh - ACM Transactions on Spatial Algorithms and Systems, 2024‏ - dl.acm.org
Accurate estimates of user location are important for many online services, including event
detection, disaster management, and determining public opinion. Neural network-based …