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Laureate CDP, Buntine W, Linger H. A systematic review of the use of topic models for short text social media analysis. Artif Intell Rev 2023:1-33. [PMID: 37362887 PMCID: PMC10150353 DOI: 10.1007/s10462-023-10471-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/14/2023] [Indexed: 06/28/2023]
Abstract
Recently, research on short text topic models has addressed the challenges of social media datasets. These models are typically evaluated using automated measures. However, recent work suggests that these evaluation measures do not inform whether the topics produced can yield meaningful insights for those examining social media data. Efforts to address this issue, including gauging the alignment between automated and human evaluation tasks, are hampered by a lack of knowledge about how researchers use topic models. Further problems could arise if researchers do not construct topic models optimally or use them in a way that exceeds the models' limitations. These scenarios threaten the validity of topic model development and the insights produced by researchers employing topic modelling as a methodology. However, there is currently a lack of information about how and why topic models are used in applied research. As such, we performed a systematic literature review of 189 articles where topic modelling was used for social media analysis to understand how and why topic models are used for social media analysis. Our results suggest that the development of topic models is not aligned with the needs of those who use them for social media analysis. We have found that researchers use topic models sub-optimally. There is a lack of methodological support for researchers to build and interpret topics. We offer a set of recommendations for topic model researchers to address these problems and bridge the gap between development and applied research on short text topic models. Supplementary Information The online version contains supplementary material available at 10.1007/s10462-023-10471-x.
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Affiliation(s)
| | - Wray Buntine
- College of Engineering and Computer Science, VinUniversity, Vinhomes Ocean Park, Gia Lam District, Hanoi 10000 Vietnam
| | - Henry Linger
- Faculty of IT, Monash University, Wellington Rd, Clayton, VIC 3800 Australia
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Westrupp EM, Greenwood CJ, Fuller-Tyszkiewicz M, Berkowitz TS, Hagg L, Youssef G. Text mining of Reddit posts: Using latent Dirichlet allocation to identify common parenting issues. PLoS One 2022; 17:e0262529. [PMID: 35108299 PMCID: PMC8809584 DOI: 10.1371/journal.pone.0262529] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2021] [Accepted: 12/28/2021] [Indexed: 11/19/2022] Open
Abstract
Parenting interventions offer an evidence-based method for the prevention and early intervention of child mental health problems, but to-date their population-level effectiveness has been limited by poor reach and engagement, particularly for fathers, working mothers, and disadvantaged families. Tailoring intervention content to parents' context offers the potential to enhance parent engagement and learning by increasing relevance of content to parents' daily experiences. However, this approach requires a detailed understanding of the common parenting situations and issues that parents face day-to-day, which is currently lacking. We sought to identify the most common parenting situations discussed by parents on parenting-specific forums of the free online discussion forum, Reddit. We aimed to understand perspectives from both mothers and fathers, and thus retrieved publicly available data from r/Daddit and r/Mommit. We used latent Dirichlet allocation to identify the 10 most common topics discussed in the Reddit posts, and completed a manual text analysis to summarize the parenting situations (defined as involving a parent and their child aged 0-18 years, and describing a potential/actual issue). We retrieved 340 (r/Daddit) and 578 (r/Mommit) original posts. A model with 31 latent Dirichlet allocation topics was best fitting, and 24 topics included posts that met our inclusion criteria for manual review. We identified 45 unique but broadly defined parenting situations. The majority of parenting situations were focused on basic childcare situations relating to eating, sleeping, routines, sickness, and toilet training; or related to how to respond to child negative emotions or difficult behavior. Most situations were discussed in relation to infant or toddler aged children, and there was high consistency in the themes raised in r/Daddit and r/Mommit. Our results offer potential to tailor parenting interventions in a meaningful way, creating opportunities to develop content and resources that are directly relevant to parents' lived experiences.
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Affiliation(s)
- Elizabeth M. Westrupp
- School of Psychology, Deakin University, Geelong, Victoria, Australia
- The Centre for Social and Early Emotional Development, Melbourne, Victoria, Australia
- Judith Lumley Centre, La Trobe University, Melbourne, Victoria, Australia
| | - Christopher J. Greenwood
- School of Psychology, Deakin University, Geelong, Victoria, Australia
- The Centre for Social and Early Emotional Development, Melbourne, Victoria, Australia
- Centre for Adolescent Health, Murdoch Children’s Research Institute, Melbourne, Victoria, Australia
| | - Matthew Fuller-Tyszkiewicz
- School of Psychology, Deakin University, Geelong, Victoria, Australia
- The Centre for Social and Early Emotional Development, Melbourne, Victoria, Australia
| | - Tomer S. Berkowitz
- School of Psychology, Deakin University, Geelong, Victoria, Australia
- The Centre for Social and Early Emotional Development, Melbourne, Victoria, Australia
| | - Lauryn Hagg
- School of Psychology, Deakin University, Geelong, Victoria, Australia
| | - George Youssef
- School of Psychology, Deakin University, Geelong, Victoria, Australia
- The Centre for Social and Early Emotional Development, Melbourne, Victoria, Australia
- Centre for Adolescent Health, Murdoch Children’s Research Institute, Melbourne, Victoria, Australia
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Halle MK, Sødal M, Forsse D, Engerud H, Woie K, Lura NG, Wagner-Larsen KS, Trovik J, Bertelsen BI, Haldorsen IS, Ojesina AI, Krakstad C. A 10-gene prognostic signature points to LIMCH1 and HLA-DQB1 as important players in aggressive cervical cancer disease. Br J Cancer 2021; 124:1690-1698. [PMID: 33723390 PMCID: PMC8110544 DOI: 10.1038/s41416-021-01305-0] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2020] [Revised: 01/26/2021] [Accepted: 02/03/2021] [Indexed: 01/31/2023] Open
Abstract
BACKGROUND Advanced cervical cancer carries a particularly poor prognosis, and few treatment options exist. Identification of effective molecular markers is vital to improve the individualisation of treatment. We investigated transcriptional data from cervical carcinomas related to patient survival and recurrence to identify potential molecular drivers for aggressive disease. METHODS Primary tumour RNA-sequencing profiles from 20 patients with recurrence and 53 patients with cured disease were compared. Protein levels and prognostic impact for selected markers were identified by immunohistochemistry in a population-based patient cohort. RESULTS Comparison of tumours relative to recurrence status revealed 121 differentially expressed genes. From this gene set, a 10-gene signature with high prognostic significance (p = 0.001) was identified and validated in an independent patient cohort (p = 0.004). Protein levels of two signature genes, HLA-DQB1 (n = 389) and LIMCH1 (LIM and calponin homology domain 1) (n = 410), were independent predictors of survival (hazard ratio 2.50, p = 0.007 for HLA-DQB1 and 3.19, p = 0.007 for LIMCH1) when adjusting for established prognostic markers. HLA-DQB1 protein expression associated with programmed death ligand 1 positivity (p < 0.001). In gene set enrichment analyses, HLA-DQB1high tumours associated with immune activation and response to interferon-γ (IFN-γ). CONCLUSIONS This study revealed a 10-gene signature with high prognostic power in cervical cancer. HLA-DQB1 and LIMCH1 are potential biomarkers guiding cervical cancer treatment.
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Affiliation(s)
- Mari K. Halle
- grid.412008.f0000 0000 9753 1393Department of Obstetrics and Gynaecology, Haukeland University Hospital, Bergen, Norway ,grid.7914.b0000 0004 1936 7443Department of Clinical Science, Centre for Cancer Biomarkers, University of Bergen, Bergen, Norway
| | - Marte Sødal
- grid.412008.f0000 0000 9753 1393Department of Obstetrics and Gynaecology, Haukeland University Hospital, Bergen, Norway ,grid.7914.b0000 0004 1936 7443Department of Clinical Science, Centre for Cancer Biomarkers, University of Bergen, Bergen, Norway
| | - David Forsse
- grid.412008.f0000 0000 9753 1393Department of Obstetrics and Gynaecology, Haukeland University Hospital, Bergen, Norway ,grid.7914.b0000 0004 1936 7443Department of Clinical Science, Centre for Cancer Biomarkers, University of Bergen, Bergen, Norway
| | - Hilde Engerud
- grid.412008.f0000 0000 9753 1393Department of Obstetrics and Gynaecology, Haukeland University Hospital, Bergen, Norway ,grid.7914.b0000 0004 1936 7443Department of Clinical Science, Centre for Cancer Biomarkers, University of Bergen, Bergen, Norway
| | - Kathrine Woie
- grid.412008.f0000 0000 9753 1393Department of Obstetrics and Gynaecology, Haukeland University Hospital, Bergen, Norway
| | - Njål G. Lura
- grid.7914.b0000 0004 1936 7443Department of Clinical Medicine, University of Bergen, Bergen, Norway ,grid.412008.f0000 0000 9753 1393Department of Radiology, Mohn Medical Imaging and Visualization Centre, Haukeland University Hospital, Bergen, Norway
| | - Kari S. Wagner-Larsen
- grid.7914.b0000 0004 1936 7443Department of Clinical Medicine, University of Bergen, Bergen, Norway ,grid.412008.f0000 0000 9753 1393Department of Radiology, Mohn Medical Imaging and Visualization Centre, Haukeland University Hospital, Bergen, Norway
| | - Jone Trovik
- grid.412008.f0000 0000 9753 1393Department of Obstetrics and Gynaecology, Haukeland University Hospital, Bergen, Norway ,grid.7914.b0000 0004 1936 7443Department of Clinical Science, Centre for Cancer Biomarkers, University of Bergen, Bergen, Norway
| | - Bjørn I. Bertelsen
- grid.412008.f0000 0000 9753 1393Department of Pathology, Haukeland University Hospital, Bergen, Norway
| | - Ingfrid S. Haldorsen
- grid.7914.b0000 0004 1936 7443Department of Clinical Medicine, University of Bergen, Bergen, Norway ,grid.412008.f0000 0000 9753 1393Department of Radiology, Mohn Medical Imaging and Visualization Centre, Haukeland University Hospital, Bergen, Norway
| | - Akinyemi I. Ojesina
- grid.265892.20000000106344187Department of Epidemiology, University of Alabama at Birmingham, Birmingham, AL USA ,grid.265892.20000000106344187O’Neal Comprehensive Cancer Center, University of Alabama at Birmingham, Birmingham, AL USA ,grid.417691.c0000 0004 0408 3720HudsonAlpha Institute for Biotechnology, Huntsville, AL USA
| | - Camilla Krakstad
- grid.412008.f0000 0000 9753 1393Department of Obstetrics and Gynaecology, Haukeland University Hospital, Bergen, Norway ,grid.7914.b0000 0004 1936 7443Department of Clinical Science, Centre for Cancer Biomarkers, University of Bergen, Bergen, Norway
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