Social media mining for identification and exploration of health-related information from pregnant women

Widespread use of social media has led to the generation of substantial amounts of information about individuals, including health-related information. Social media provides the opportunity to study health-related information about selected population groups who may be of interest for a particular study. In this paper, we explore the possibility of utilizing social media to perform targeted data collection and analysis from a particular population group -- pregnant women. We hypothesize that we can use social media to identify cohorts of pregnant women and follow them over time to analyze crucial health-related information. To identify potentially pregnant women, we employ simple rule-based searches that attempt to detect pregnancy announcements with moderate precision. To further filter out false positives and noise, we employ a supervised classifier using a small number of hand-annotated data. We then collect their posts over time to create longitudinal health timelines and attempt to divide the timelines into different pregnancy trimesters. Finally, we assess the usefulness of the timelines by performing a preliminary analysis to estimate drug intake patterns of our cohort at different trimesters. Our rule-based cohort identification technique collected 53,820 users over thirty months from Twitter. Our pregnancy announcement classification technique achieved an F-measure of 0.81 for the pregnancy class, resulting in 34,895 user timelines. Analysis of the timelines revealed that pertinent health-related information, such as drug-intake and adverse reactions can be mined from the data. Our approach to using user timelines in this fashion has produced very encouraging results and can be employed for other important tasks where cohorts, for which health-related information may not be available from other sources, are required to be followed over time to derive population-based estimates.Comment: 9 page

Knowledge will Propel Machine Understanding of Content: Extrapolating from Current Examples

Machine Learning has been a big success story during the AI resurgence. One particular stand out success relates to learning from a massive amount of data. In spite of early assertions of the unreasonable effectiveness of data, there is increasing recognition for utilizing knowledge whenever it is available or can be created purposefully. In this paper, we discuss the indispensable role of knowledge for deeper understanding of content where (i) large amounts of training data are unavailable, (ii) the objects to be recognized are complex, (e.g., implicit entities and highly subjective content), and (iii) applications need to use complementary or related data in multiple modalities/media. What brings us to the cusp of rapid progress is our ability to (a) create relevant and reliable knowledge and (b) carefully exploit knowledge to enhance ML/NLP techniques. Using diverse examples, we seek to foretell unprecedented progress in our ability for deeper understanding and exploitation of multimodal data and continued incorporation of knowledge in learning techniques.Comment: Pre-print of the paper accepted at 2017 IEEE/WIC/ACM International Conference on Web Intelligence (WI). arXiv admin note: substantial text overlap with arXiv:1610.0770

Understanding Psycholinguistic Behavior of predominant drunk texters in Social Media

In the last decade, social media has evolved as one of the leading platform to create, share, or exchange information; it is commonly used as a way for individuals to maintain social connections. In this online digital world, people use to post texts or pictures to express their views socially and create user-user engagement through discussions and conversations. Thus, social media has established itself to bear signals relating to human behavior. One can easily design user characteristic network by scraping through someone's social media profiles. In this paper, we investigate the potential of social media in characterizing and understanding predominant drunk texters from the perspective of their social, psychological and linguistic behavior as evident from the content generated by them. Our research aims to analyze the behavior of drunk texters on social media and to contrast this with non-drunk texters. We use Twitter social media to obtain the set of drunk texters and non-drunk texters and show that we can classify users into these two respective sets using various psycholinguistic features with an overall average accuracy of 96.78% with very high precision and recall. Note that such an automatic classification can have far-reaching impact - (i) on health research related to addiction prevention and control, and (ii) in eliminating abusive and vulgar contents from Twitter, borne by the tweets of drunk texters.Comment: 6 pages, 8 Figures, ISCC 2018 Workshops - ICTS4eHealth 201

Justice in Review: New Trends in State Sentencing and Corrections 2014-2015

In 2014 and 2015, 46 states enacted at least 201 bills, executive orders, and ballot initiatives to reform at least one aspect of their sentencing and corrections systems. In conducting this review of state criminal justice reforms, Vera found that most of the policy changes focused on three areas: creating or expanding opportunities to divert people away from the criminal justice system; reducing prison populations by enacting sentencing reform, expanding opportunities for early release from prison, and reducing the number of people admitted to prison for violating the terms of their community supervision; and supporting reentry into the community from prison. By providing concise summaries of representative reforms in each of these areas, this report serves as a practical guide for other state and federal policymakers looking to affect similar changes in criminal justice policy

Consolidated List of Requirements

This document is a consolidated catalogue of requirements for the Electronic Health Care Record (EHCR) and Electronic Health Care Record Architecture (EHCRA), gleaned largely from work done in the EU Framework III and IV programmes and CEN, but also including input from other sources including world-wide standardisation initiatives. The document brings together the relevant work done into a classified inventory of requirements to inform the on-going standardisation process as well as act as a guide to future implementation of EHCRA-based systems. It is meant as a contribution both to understanding of the standard and to the work that is being considered to improve the standard. Major features include the classification into issues affecting the Health Care Record, the EHCR, EHCR processing, EHCR interchange and the sharing of health care information and EHCR systems. The principal information sources are described briefly. It is offered as documentation that is complementary to the four documents of the ENV 13606 Parts I-IV produced by CEN Pts 26,27,28,29. The requirements identified and classified in this deliverable are referenced in other deliverables

Consumer use and response to online third-party raw DNA interpretation services

This study was funded in part by a pilot grant from the Boston University School of Public Health. (Boston University School of Public Health)Published versio

E-word of mouth: building sustainable and trustworthy relationships with customers in a highly regulated on-line environment

With the increasing popularity of social media, consumers now turn to different online discussion forums, consumer review sites, weblogs, social network sites and so on to seek product information and share their own experiences (Cheung and Thadani, 2010; Davies, 2008). Consequently, companies today face an increasingly difficult challenge: how to communicate with consumers online in a way that encourages trust and engagement? What may make things even more complicated is that many companies are now operating in a highly regulated environment, with the healthcare industry a typical example of this (Choi and Lee, 2007; Huh and Langteau, 2007; Nielson, 2008; von Knoop et al., 2003). Thus, pharmaceutical marketers and brand managers must understand how to communicate effectively in a highly regulated online environment. This short report aims to help such companies to build a sustainable and trustworthy relationship with their customers online. To do so, the report considers the subject from the perspective of a pharmaceutical company. It will first discuss the current regulations around the healthcare industry, highlighting the constraints pharmaceutical marketers need to face. Then, it will review current literature discussing healthcare consumers’ online behaviour. In particular, it will focus on consumers’ negative comments and their possible impact on the business. Finally, the report concludes with some suggestions about how to cope with negative comments online and build a reliable relationship with customers