Assessing the Possible Relationship between the Sentiment of Church-related Tweets and Church Growth

2016 ◽  
Vol 46 (1) ◽  
pp. 37-49 ◽  
Author(s):  
Anthony-Paul Cooper
Keyword(s):  
Social Media ◽  
United Kingdom ◽  
Church Growth ◽  
Significant Relationship ◽  
Geographical Area ◽  
The Body ◽  
Social Media Data ◽  
Body Of Knowledge ◽  
The United Kingdom ◽  
Media Data

This article examines the possible relationship between the sentiment of church-related tweets and church growth. It finds that within the sample of tweets analysed, there is a statistically significant relationship between the sentiment of a church-related tweet and the presence of church growth in the geographical area from which the tweet was posted. This work builds on the body of knowledge surrounding church growth and decline in the United Kingdom, by seeking to better understand how new sources of data, in this case freely available social media data, can be used to gain a better understanding of the behaviours of churches which regularly form, merge, move, split and close.

scholarly journals Identifying Sleep-Deprived Authors of Tweets: Prospective Study

10.2196/13076 ◽  
2019 ◽  
Vol 6 (12) ◽  
pp. e13076
Author(s):  
Sara Melvin ◽  
Amanda Jamal ◽  
Kaitlyn Hill ◽  
Wei Wang ◽  
Sean D Young
Keyword(s):  
Neural Network ◽  
Social Media ◽  
Sleep Deprivation ◽  
Undergraduate Students ◽  
Area Under The Curve ◽  
The Body ◽  
First Year ◽  
Social Media Data ◽  
Tracking Devices ◽  
Media Data

Background Social media data can be explored as a tool to detect sleep deprivation. First-year undergraduate students in their first quarter were invited to wear sleep-tracking devices (Basis; Intel), allow us to follow them on Twitter, and complete weekly surveys regarding their sleep. Objective This study aimed to determine whether social media data can be used to monitor sleep deprivation. Methods The sleep data obtained from the device were utilized to create a tiredness model that aided in labeling the tweets as sleep deprived or not at the time of posting. Labeled data were used to train and test a gated recurrent unit (GRU) neural network as to whether or not study participants were sleep deprived at the time of posting. Results Results from the GRU neural network suggest that it is possible to classify the sleep-deprivation status of a tweet’s author with an average area under the curve of 0.68. Conclusions It is feasible to use social media to identify students’ sleep deprivation. The results add to the body of research suggesting that social media data should be further explored as a potential source for monitoring health.

scholarly journals Identifying Sleep-Deprived Authors of Tweets: Prospective Study (Preprint)

2018 ◽  
Author(s):  
Sara Melvin ◽  
Amanda Jamal ◽  
Kaitlyn Hill ◽  
Wei Wang ◽  
Sean D Young
Keyword(s):  
Neural Network ◽  
Social Media ◽  
Sleep Deprivation ◽  
Undergraduate Students ◽  
Area Under The Curve ◽  
The Body ◽  
First Year ◽  
Social Media Data ◽  
Tracking Devices ◽  
Media Data

BACKGROUND Social media data can be explored as a tool to detect sleep deprivation. First-year undergraduate students in their first quarter were invited to wear sleep-tracking devices (Basis; Intel), allow us to follow them on Twitter, and complete weekly surveys regarding their sleep. OBJECTIVE This study aimed to determine whether social media data can be used to monitor sleep deprivation. METHODS The sleep data obtained from the device were utilized to create a tiredness model that aided in labeling the tweets as sleep deprived or not at the time of posting. Labeled data were used to train and test a gated recurrent unit (GRU) neural network as to whether or not study participants were sleep deprived at the time of posting. RESULTS Results from the GRU neural network suggest that it is possible to classify the sleep-deprivation status of a tweet’s author with an average area under the curve of 0.68. CONCLUSIONS It is feasible to use social media to identify students’ sleep deprivation. The results add to the body of research suggesting that social media data should be further explored as a potential source for monitoring health.

scholarly journals ADMISSIBILITY AND AUTHENTICITY OF ELECTRONIC EVIDENCE IN THE COURTS OF MALAYSIA AND UNITED KINGDOM

2019 ◽  
pp. 121-129
Author(s):  
Ani Munirah Mohamad
Keyword(s):  
United Kingdom ◽  
The Body ◽  
Legal Research ◽  
Electronic Evidence ◽  
Body Of Knowledge ◽  
The United Kingdom ◽  
Legal Provisions ◽  
The Uk ◽  
Criminal Matters ◽  
Law Of Evidence

This concept paper elaborates on two main aspects of electronic evidence (1) the admissibility of such evidence in the courts of law, and (2) its authenticity as evidence for the consideration of the courts. In both aspects, the scope of discussion would be the laws in Malaysia and in the United Kingdom (UK). In essence, the relevant rules providing for electronic evidence in Malaysia is the Evidence Act 1950, meanwhile for the case of the UK, the Civil Evidence Act 1995 and Police and Criminal Evidence Act 1984 which provide for electronic evidence in civil and criminal matters respectively. Engaging in comparative legal research methods, and purely library-based, the relevant legal provisions for each jurisdiction are elaborated, and numerous cases are discussed in this paper to illustrate the application of such sections in admitting and authenticating electronic evidence in the Courts of Malaysia and the UK. Hopefully, this paper would become a contribution to the body of knowledge and contribute towards more in-depth research in the area of law of evidence.

An Evaluation of a Preceptorship Programme for Newly Qualified Occupational Therapists

2009 ◽  
Vol 72 (9) ◽  
pp. 384-392 ◽  
Author(s):  
Mary Morley
Keyword(s):  
United Kingdom ◽  
National Health Service ◽  
Health Service ◽  
Occupational Therapists ◽  
The Body ◽  
Structured Interviews ◽  
Body Of Knowledge ◽  
The United Kingdom ◽  
Transitional Experience ◽  
Definition Of

Following the introduction of preceptorship as a requirement for most newly qualified practitioners in the National Health Service in the United Kingdom, a preceptorship programme for occupational therapists was designed. This was the first of its kind within occupational therapy and was endorsed by the College of Occupational Therapists. Participation in preceptorship was intended to ease the transition of newly qualified occupational therapists. This paper offers a definition of preceptorship for the profession in the United Kingdom and reports on a small qualitative study that evaluated the extent to which the interventions of the preceptorship programme ameliorated the challenges of transition. The evaluation was conducted within a realist framework. Data were collected by semi-structured interviews from four pairs of newly qualified occupational therapists and preceptors during the pilot year. The findings suggest that the preceptorship programme was successful in supporting the development of new practitioners and that implementation was optimised through strong leadership, a learning culture and positive supervision. This paper contributes to the body of knowledge relating to the transitional experience of occupational therapists and recommends changes to the programme to optimise its effectiveness for practice.

Smart De-Identification of Social Media Data

2014 ◽  
Author(s):  
Kathleen M. Carley ◽  
L. R. Carley ◽  
Jonathan Storrick
Keyword(s):  
Social Media ◽  
Social Media Data ◽  
Media Data

Mining Social Media Data to Study the Consequences of Dementia Diagnosis on Caregivers and Relatives (Preprint)

2018 ◽  
Author(s):  
Anika Oellrich ◽  
George Gkotsis ◽  
Richard James Butler Dobson ◽  
Tim JP Hubbard ◽  
Rina Dutta
Keyword(s):  
Social Media ◽  
Family Relationships ◽  
Text Processing ◽  
Automated Analysis ◽  
Health Concern ◽  
Dementia Diagnosis ◽  
Data Set ◽  
Social Media Data ◽  
Real Time Processing ◽  
Media Data

BACKGROUND Dementia is a growing public health concern with approximately 50 million people affected worldwide in 2017 and this number is expected to reach more than 131 million by 2050. The toll on caregivers and relatives cannot be underestimated as dementia changes family relationships, leaves people socially isolated, and affects the finances of all those involved. OBJECTIVE The aim of this study was to explore using automated analysis (i) the age and gender of people who post to the social media forum Reddit about dementia diagnoses, (ii) the affected person and their diagnosis, (iii) relevant subreddits authors are posting to, (iv) the types of messages posted and (v) the content of these posts. METHODS We analysed Reddit posts concerning dementia diagnoses. We used a previously developed text analysis pipeline to determine attributes of the posts as well as their authors to characterise online communications about dementia diagnoses. The posts were also examined by manual curation for the diagnosis provided and the person affected. Furthermore, we investigated the communities these people engage in and assessed the contents of the posts with an automated topic gathering technique. RESULTS Our results indicate that the majority of posters in our data set are women, and it is mostly close relatives such as parents and grandparents that are mentioned. Both the communities frequented and topics gathered reflect not only the sufferer's diagnosis but also potential outcomes, e.g. hardships experienced by the caregiver. The trends observed from this dataset are consistent with findings based on qualitative review, validating the robustness of social media automated text processing. CONCLUSIONS This work demonstrates the value of social media data sources as a resource for in-depth studies of those affected by a dementia diagnosis and the potential to develop novel support systems based on their real time processing in line with the increasing digitalisation of medical care.

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