OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Prospective associations of text‐message‐based sentiment with symptoms of depression, generalized anxiety, and social anxiety
Caitlin A. Stamatis, Jonah Meyerhoff, Tingting Liu, et al.
Depression and Anxiety (2022) Vol. 39, Iss. 12, pp. 794-804
Open Access | Times Cited: 32

Showing 1-25 of 32 citing articles:

Differential temporal utility of passively sensed smartphone features for depression and anxiety symptom prediction: a longitudinal cohort study
Caitlin A. Stamatis, Jonah Meyerhoff, Yixuan Meng, et al.
npj Mental Health Research (2024) Vol. 3, Iss. 1
Open Access | Times Cited: 13

Measuring algorithmic bias to analyze the reliability of AI tools that predict depression risk using smartphone sensed-behavioral data
Daniel A. Adler, Caitlin A. Stamatis, Jonah Meyerhoff, et al.
npj Mental Health Research (2024) Vol. 3, Iss. 1
Open Access | Times Cited: 6

Analyzing text message linguistic features: Do people with depression communicate differently with their close and non-close contacts?
Jonah Meyerhoff, Tingting Liu, Caitlin A. Stamatis, et al.
Behaviour Research and Therapy (2023) Vol. 166, pp. 104342-104342
Closed Access | Times Cited: 15

The Promise of Affective Language for Identifying and Intervening on Psychopathology
Erik C. Nook
Affective Science (2023) Vol. 4, Iss. 3, pp. 517-521
Open Access | Times Cited: 13

Punctuation and lexicon aid representation: A hybrid model for short text sentiment analysis on social media platform
Zhenyu Li, Zongfeng Zou
Journal of King Saud University - Computer and Information Sciences (2024) Vol. 36, Iss. 3, pp. 102010-102010
Open Access | Times Cited: 4

Using natural language processing to identify patterns associated with depression, anxiety, and stress symptoms during the COVID-19 pandemic
Abigail Beech, Haoxue Fan, Jocelyn Shu, et al.
Journal of Affective Disorders (2025)
Closed Access

Utilizing natural language processing for precision prevention of mental health disorders among youth: A systematic review
Sheriff Tolulope Ibrahim, Madeline Li, Jamin Patel, et al.
Computers in Biology and Medicine (2025) Vol. 188, pp. 109859-109859
Open Access

The Relation between passively collected GPS mobility metrics and depressive symptoms: A systematic review and meta-analysis. (Preprint)
Yannik Terhorst, Johannes Knauer, Paula Philippi, et al.
Journal of Medical Internet Research (2024) Vol. 26, pp. e51875-e51875
Open Access | Times Cited: 3

Capturing mood dynamics through adolescent smartphone social communication.
Lilian Y. Li, Esha Trivedi, Fiona Helgren, et al.
Journal of Psychopathology and Clinical Science (2023) Vol. 132, Iss. 8, pp. 1072-1084
Open Access | Times Cited: 7

A comparison of linguistic patterns between individuals with current major depressive disorder, past major depressive disorder, and controls in a virtual, psychiatric research interview
Lisette Corbin, Emily Griner, Salman Seyedi, et al.
Journal of Affective Disorders Reports (2023) Vol. 14, pp. 100645-100645
Open Access | Times Cited: 7

Detecting adolescent depression through passive monitoring of linguistic markers in smartphone communication
Carter J. Funkhouser, Esha Trivedi, Lilian Y. Li, et al.
Journal of Child Psychology and Psychiatry (2023) Vol. 65, Iss. 7, pp. 932-941
Open Access | Times Cited: 6

Predicting dimensions of depression from smartphone data
Vincent Holstein, Samir Akre, Ramona Leenings, et al.
medRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access | Times Cited: 1

Reading Between the Lines: Identifying the Linguistic Markers of Anhedonia for the Stratification of Depression
Bridianne O’Dea, Taylor A. Braund, Philip J. Batterham, et al.
(2024), pp. 1-13
Open Access | Times Cited: 1

Language sentiment predicts changes in depressive symptoms
Jihyun K. Hur, Joseph Heffner, Gloria Feng, et al.
Proceedings of the National Academy of Sciences (2024) Vol. 121, Iss. 39
Open Access | Times Cited: 1

Predicting Affective States from Screen Text Sentiment
Songyan Teng, Tianyi Zhang, Simon D’Alfonso, et al.
(2024), pp. 384-390
Open Access | Times Cited: 1

Linguistic variables and gender differences within a messenger-based psychosocial chat counseling service for children and adolescents: A cross-sectional study (Preprint)
Zeki Efe, Sabrina Baldofski, Elisabeth Kohls, et al.
JMIR Formative Research (2023) Vol. 8, pp. e51795-e51795
Open Access | Times Cited: 2

Depression Detection on e-Risk 2017 using Long Short-term Memory Models
Farnaz Sheikhi, Laya Fakher, Danial Chekani
(2024)
Closed Access

Measuring algorithmic bias to analyze the reliability of AI tools that predict depression risk using smartphone sensed-behavioral data
Daniel A. Adler, Caitlin A. Stamatis, Jonah Meyerhoff, et al.
Research Square (Research Square) (2024)
Open Access

The (not-so) valid and reliable linguistic markers of depression and anxiety in symptomatic adults: A randomised cross over trial
Bridianne O’Dea, Philip J. Batterham, Taylor A. Braund, et al.
Research Square (Research Square) (2024)
Closed Access

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