Martin Sykora
Biographic Data
| ID | 355931 |
|---|---|
| NAME | Martin Sykora |
| GIVEN NAMES | Martin |
| FAMILY NAME | Sykora |
| SIGNATURE | SYKORA M |
| AFFILIATIONS | Loughborough University |
| ORCID | 0000-0002-5363-5857 |
| VERIFIED | Yes |
| TOTAL WORKS | 14 |
| TOTAL CITATIONS | 21 |
| AUTHOR COUNT | 14 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2017 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 3 |
Social Identities in Twitter Issue Publics
In the digital age, platforms such as Twitter foster the emergence of fragmented issue-based communities online, intersecting with traditional media and broader national discourse. However, these digital public spheres often deviate from idealised concepts like those proposed by Habermas, showcasing uncivil discourse and participatory disparities. Recent research highlights a subset of hyperactive users on Twitter who monopolise discussions on co…
Smart Citizens Enabling Resilient Neighbourhoods (SCERN)
Deliberative Qualities of Online Abortion Discourse
This paper provides a big-data-scale assessment of the deliberative qualities of online abortion discussions on Twitter in the United States (2020) and Ireland (2018) by specifically focusing on two standards: civility and tolerance for constructive disagreements. Using diverse computational methods and classification, our regression analysis provides mixed evaluations. We find that incivility and intolerance are uncommon behaviours in American a…
Plasma concentrations of SSRI/SNRI after bariatric surgery and the effects on depressive symptoms
In patients undergoing bariatric surgery plasma concentrations of SSRI/SNRI decrease significantly by about 25% mainly during the first 4 weeks postoperatively with wide individual variation, but without correlation to the severity of depression or weight loss
The Role of Social Media in Building Pandemic Resilience in an Urban Community
This paper explores the influence of social media in fostering resilience within an urban spatial context, specifically in Bangalore, India, during the COVID-19 lockdown, a period marked by a surge in digital communication due to movement restrictions. To control the rapid spread of the virus, over 1.38 billion people were given stay-at-home orders by the government of India during the onset of the pandemic. The restrictions in movement forced in…
Reproducibility and Scientific Integrity of Big Data Research in Urban Public Health and Digital Epidemiology
The emergence of big data science presents a unique opportunity to improve public-health research practices. Because working with big data is inherently complex, big data research must be clear and transparent to avoid reproducibility issues and positively impact population health. Timely implementation of solution-focused approaches is critical as new data sources and methods take root in public-health research, including urban public health and…
Detecting Suicide Ideation in the Era of Social Media
Social media platforms are increasingly used across many population groups not only to communicate and consume information, but also to express symptoms of psychological distress and suicidal thoughts. The detection of suicidal ideation (SI) can contribute to suicide prevention. Twitter data suggesting SI have been associated with negative emotions (e.g., shame, sadness) and a number of geographical and ecological variables (e.g., geographic loca…
Space-Time Dependence of Emotions on Twitter after a Natural Disaster
Natural disasters can have significant consequences for population mental health. Using a digital spatial epidemiologic approach, this study documents emotional changes over space and time in the context of a large-scale disaster. Our aims were to (a) explore the spatial distribution of negative emotional expressions of Twitter users before, during, and after Superstorm Sandy in New York City (NYC) in 2012 and (b) examine potential correlations b…
Real-time geospatial surveillance of localized emotional stress responses to Covid-19
A qualitative analysis of sarcasm, irony and related #hashtags on Twitter
As the use of automated social media analysis tools surges, concerns over accuracy of analytics have increased. Some tentative evidence suggests that sarcasm alone could account for as much as a 50% drop in accuracy when automatically detecting sentiment. This paper assesses and outlines the prevalence of sarcastic and ironic language within social media posts. Several past studies proposed models for automatic sarcasm and irony detection for sen…
A unified ecological framework for studying effects of digital places on well-being
Spatio-Temporal Distribution of Negative Emotions in New York City After a Natural Disaster as Seen in Social Media
Disasters have substantial consequences for population mental health. We used Twitter to (1) extract negative emotions indicating discomfort in New York City (NYC) before, during, and after Superstorm Sandy in 2012. We further aimed to (2) identify whether pre- or peri-disaster discomfort were associated with peri- or post-disaster discomfort, respectively, and to (3) assess geographic variation in discomfort across NYC census tracts over time. O…
Social media analytics in museums
Museums have a remit to inspire visitors. However, inspiration is a complex, subjective construct and analyses of inspiration are often laborious. Increased use of social media by museums and visitors may provide new opportunities to collect evidence of inspiration more efficiently. This research investigates the feasibility of a system based on knowledge patterns from FrameNet – a lexicon structured around models of typical experiences – to extr…
Big data opportunities for social behavioral and mental health research
Social media analytics in museums
Museums have a remit to inspire visitors. However, inspiration is a complex, subjective construct and analyses of inspiration are often laborious. Increased use of social media by museums and visitors may provide new opportunities to collect evidence of inspiration more efficiently. This research investigates the feasibility of a system based on knowledge patterns from FrameNet – a lexicon structured around models of typical experiences – to extr…
A qualitative analysis of sarcasm, irony and related #hashtags on Twitter
As the use of automated social media analysis tools surges, concerns over accuracy of analytics have increased. Some tentative evidence suggests that sarcasm alone could account for as much as a 50% drop in accuracy when automatically detecting sentiment. This paper assesses and outlines the prevalence of sarcastic and ironic language within social media posts. Several past studies proposed models for automatic sarcasm and irony detection for sen…
A unified ecological framework for studying effects of digital places on well-being
Big data opportunities for social behavioral and mental health research
Social media analytics in museums
Museums have a remit to inspire visitors. However, inspiration is a complex, subjective construct and analyses of inspiration are often laborious. Increased use of social media by museums and visitors may provide new opportunities to collect evidence of inspiration more efficiently. This research investigates the feasibility of a system based on knowledge patterns from FrameNet – a lexicon structured around models of typical experiences – to extr…
Big data opportunities for social behavioral and mental health research
Spatio-Temporal Distribution of Negative Emotions in New York City After a Natural Disaster as Seen in Social Media
Disasters have substantial consequences for population mental health. We used Twitter to (1) extract negative emotions indicating discomfort in New York City (NYC) before, during, and after Superstorm Sandy in 2012. We further aimed to (2) identify whether pre- or peri-disaster discomfort were associated with peri- or post-disaster discomfort, respectively, and to (3) assess geographic variation in discomfort across NYC census tracts over time. O…
A unified ecological framework for studying effects of digital places on well-being
A qualitative analysis of sarcasm, irony and related #hashtags on Twitter
As the use of automated social media analysis tools surges, concerns over accuracy of analytics have increased. Some tentative evidence suggests that sarcasm alone could account for as much as a 50% drop in accuracy when automatically detecting sentiment. This paper assesses and outlines the prevalence of sarcastic and ironic language within social media posts. Several past studies proposed models for automatic sarcasm and irony detection for sen…
Space-Time Dependence of Emotions on Twitter after a Natural Disaster
Natural disasters can have significant consequences for population mental health. Using a digital spatial epidemiologic approach, this study documents emotional changes over space and time in the context of a large-scale disaster. Our aims were to (a) explore the spatial distribution of negative emotional expressions of Twitter users before, during, and after Superstorm Sandy in New York City (NYC) in 2012 and (b) examine potential correlations b…
Real-time geospatial surveillance of localized emotional stress responses to Covid-19
Detecting Suicide Ideation in the Era of Social Media
Social media platforms are increasingly used across many population groups not only to communicate and consume information, but also to express symptoms of psychological distress and suicidal thoughts. The detection of suicidal ideation (SI) can contribute to suicide prevention. Twitter data suggesting SI have been associated with negative emotions (e.g., shame, sadness) and a number of geographical and ecological variables (e.g., geographic loca…
Deliberative Qualities of Online Abortion Discourse
This paper provides a big-data-scale assessment of the deliberative qualities of online abortion discussions on Twitter in the United States (2020) and Ireland (2018) by specifically focusing on two standards: civility and tolerance for constructive disagreements. Using diverse computational methods and classification, our regression analysis provides mixed evaluations. We find that incivility and intolerance are uncommon behaviours in American a…
Plasma concentrations of SSRI/SNRI after bariatric surgery and the effects on depressive symptoms
In patients undergoing bariatric surgery plasma concentrations of SSRI/SNRI decrease significantly by about 25% mainly during the first 4 weeks postoperatively with wide individual variation, but without correlation to the severity of depression or weight loss
The Role of Social Media in Building Pandemic Resilience in an Urban Community
This paper explores the influence of social media in fostering resilience within an urban spatial context, specifically in Bangalore, India, during the COVID-19 lockdown, a period marked by a surge in digital communication due to movement restrictions. To control the rapid spread of the virus, over 1.38 billion people were given stay-at-home orders by the government of India during the onset of the pandemic. The restrictions in movement forced in…
Reproducibility and Scientific Integrity of Big Data Research in Urban Public Health and Digital Epidemiology
The emergence of big data science presents a unique opportunity to improve public-health research practices. Because working with big data is inherently complex, big data research must be clear and transparent to avoid reproducibility issues and positively impact population health. Timely implementation of solution-focused approaches is critical as new data sources and methods take root in public-health research, including urban public health and…
Social Identities in Twitter Issue Publics
In the digital age, platforms such as Twitter foster the emergence of fragmented issue-based communities online, intersecting with traditional media and broader national discourse. However, these digital public spheres often deviate from idealised concepts like those proposed by Habermas, showcasing uncivil discourse and participatory disparities. Recent research highlights a subset of hyperactive users on Twitter who monopolise discussions on co…
Smart Citizens Enabling Resilient Neighbourhoods (SCERN)
Computer Science (10 works) · Social media (10 works) · World Wide Web (8 works) · Data science (7 works) · Sociology (7 works) · Geography (6 works) · Political science (6 works) · Psychology (6 works) · Social Psychology (6 works) · Social Psychology (5 works)