scholarly journals Assessment of Antipsychotic Medications on Social Media: Machine Learning Study

2021 ◽  
Vol 12 ◽  
Author(s):  
Miguel A. Alvarez-Mon ◽  
Carolina Donat-Vargas ◽  
Javier Santoma-Vilaclara ◽  
Laura de Anta ◽  
Javier Goena ◽  
...  
Keyword(s):  
Social Media ◽  
Negative Impact ◽  
Online Environment ◽  
First Line ◽  
Antipsychotic Medications ◽  
Twitter User ◽  
Medical Institutions ◽  
Twitter Users ◽  
User Perspectives ◽  
First Line Treatment

Background: Antipsychotic medications are the first-line treatment for schizophrenia. However, non-adherence is frequent despite its negative impact on the course of the illness. In response, we aimed to investigate social media posts about antipsychotics to better understand the online environment in this regard.Methods: We collected tweets containing mentions of antipsychotic medications posted between January 1st 2019 and October 31st 2020. The content of each tweet and the characteristics of the users were analyzed as well as the number of retweets and likes generated.Results: Twitter users, especially those identified as patients, showed an interest in antipsychotic medications, mainly focusing on the topics of sexual dysfunction and sedation. Interestingly, paliperidone, despite being among one of the newest antipsychotics, accounted for a low number of tweets and did not generate much interest. Conversely, retweet and like ratios were higher in those tweets asking for or offering help, in those posted by institutions and in those mentioning cognitive complaints. Moreover, health professionals did not have a strong presence in tweet postings, nor did medical institutions. Finally, trivialization was frequently observed.Conclusion: This analysis of tweets about antipsychotic medications provides insights into experiences and opinions related to this treatment. Twitter user perspectives therefore constitute a valuable input that may help to improve clinicians' knowledge of antipsychotic medications and their communication with patients regarding this treatment.

scholarly journals Comparison of risperidone, olanzapine and quetiapine: effects on body weight, serum blood glucose and prolactin

2008 ◽  
Vol 5 (3) ◽  
pp. 71-73
Author(s):  
Haroon Rashid Chaudhry ◽  
Nadia Arshad ◽  
Saima Niaz ◽  
Tahir Suleman ◽  
Khalid A. Mufti
Keyword(s):  
Body Weight ◽  
Blood Glucose ◽  
Chronic Illness ◽  
Economic Consequences ◽  
Line Treatment ◽  
First Line ◽  
Antipsychotic Medications ◽  
The Past ◽  
Atypical Antipsychotic Medications ◽  
First Line Treatment

Schizophrenia is a chronic illness with a lifetime prevalence of 1% and with serious physical, social and economic consequences. Over the past decade, atypical antipsychotic medications have become the first-line treatment for schizophrenia (Breier et al, 2005).

scholarly journals Understanding users Display-Name Consistency across Social Networks

2019 ◽  
Vol 8 (5S3) ◽  
pp. 471-476
Keyword(s):  
Social Networks ◽  
Social Media ◽  
Social Networking ◽  
Experimental Results ◽  
Personal Attributes ◽  
Media Content ◽  
Social Networking Services ◽  
Twitter User ◽  
The Social ◽  
Twitter Users

Online users create their profiles on numerous social platforms to get benefits of various types of social media content. During online profile creation, the user selects a username and feeds his/her personal details like name, location, email, etc. As different social networking services acquire common personal attributes of the same user and present them in a variety of formats. To understand the availability and similarity of personal attributes across various social networking services, we propose a method that uses the different distance measuring algorithms to determine the display-name similarity across social networks. From the experimental results, it is found that at least twenty percent GooglePlus-Facebook and Facebook-Twitter users select the same display name, while forty five percent Google and Twitter user select identical name across both the social networks.

scholarly journals Sentiment Analysis of West Java International Airport (Bijb) Kertajati on Twitter

2020 ◽  
Vol 4 (2) ◽  
pp. 176-182
Author(s):  
Oka Intan ◽  
Sri Widiyanesti
Keyword(s):  
Social Media ◽  
Sentiment Analysis ◽  
Rapid Development ◽  
West Java ◽  
Word Cloud ◽  
Twitter User ◽  
The Social ◽  
Twitter Users ◽  
Negative Sentiment

The rapid development of technology allows everything to accessed by the internet that causes many users of social media and one of the social media is Twitter. An interesting topic to discuss on Twitter is about new and fresh things that attract many users to get involved. One of the things that attract Twitter users is the construction of a new airport, namely Kertajati Airport, which has some problems with airport activities, such as the small number of visitors, lonely conditions of the airport, and decreased number of routes. This study aims to find out Twitter user sentiments towards Kertajati Airport in West Java to know the quality of Kertajati Airport. The method used in this study is sentiment analysis by looking at the calculation of how many positive and negative sentiment have been obtained with the most result so it can reflect the quality of Kertajati Airport and then there is a word cloud to see the spread of word related to sentiment. The results of this study indicate that the quality of the Kertajati Airport cannot be said to be good because the results of the sentiment analysis found that negative sentiments have more percentages than positive sentiments

Recurrent Neural Network (RNN) to Analyse Mental Behaviour in Social Media

2021 ◽  
Vol 13 (3) ◽  
pp. 1-11
Author(s):  
Hadj Ahmed Bouarara
Keyword(s):  
Neural Network ◽  
Mental Health ◽  
Social Media ◽  
Recurrent Neural Network ◽  
Mental Health Problems ◽  
Negative Impact ◽  
Psychological Problem ◽  
Twitter Users ◽  
British Study ◽  
F Measure

A recent British study of people between the ages of 14 and 35 has shown that social media has a negative impact on mental health. The purpose of the paper is to detect people with mental disorders' behaviour in social media in order to help Twitter users in overcoming their mental health problems such as anxiety, phobia, depression, paranoia. The authors have adapted the recurrent neural network (RNN) in order to prevent the situations of threats, suicide, loneliness, or any other form of psychological problem through the analysis of tweets. The obtained results were validated by different experimental measures such as f-measure, recall, precision, entropy, accuracy. The RNN gives best results with 85% of accuracy compared to other techniques in literature such as social cockroaches, decision tree, and naïve Bayes.

The Usage of Twitter in Small Businesses for Countries with a Low Twitter User Base

2020 ◽  
Vol 9 (4) ◽  
pp. 01-10
Author(s):  
Munif Mohammed Ali Al-Zoubi ◽  
Keyword(s):  
Social Media ◽  
Marketing Strategy ◽  
Small Businesses ◽  
Design Methodology ◽  
Secondary Data ◽  
Online Marketing ◽  
Twitter User ◽  
Twitter Users

This research aims to find the differences in the use of Twitter between small and large businesses, and how small businesses (SMEs) can follow and learn from their larger counterparts or refuse to use this platform due to the small number of Twitter users in that country. Design/methodology/approach: The research will use data obtained through multiple interviews with businesses in Amman Jordan, and uses secondary data gathered through a questionnaire regarding the usage of Twitter in the day to day life, Jordan is used as an example of a country with a low Twitter base. Keywords: Social Media, Twitter, e-WOM, Online Marketing Strategy, SMEs’.

Sentiment Analysis Using Machine Learning Algorithms and Text Mining to Detect Symptoms of Mental Difficulties Over Social Media

2021 ◽  
Vol 12 (2) ◽  
pp. 1-15
Author(s):  
Hadj Ahmed Bouarara
Keyword(s):  
Mental Health ◽  
Machine Learning ◽  
Social Media ◽  
Text Mining ◽  
Mental Health Problems ◽  
Negative Impact ◽  
Learning Algorithms ◽  
Machine Learning Algorithms ◽  
Nearest Neighbours ◽  
Twitter Users

A recent British study of people between the ages of 14 and 35 has shown that social media has a negative impact on mental health. The purpose of the paper is to detect people with mental disorders' behavior in social media in order to help Twitter users in overcoming their mental health problems such as anxiety, phobia, depression, paranoia, etc. For this, the author used text mining and machine learning algorithms (naïve Bayes, k-nearest neighbours) to analyse tweets. The obtained results were validated using different evaluation measures such as f-measure, recall, precision, entropy, etc.

scholarly journals SENTIMENT ANALYSIS OF CURRENT TRENDING TOPICS ON TWITTER USER BASE

2021 ◽  
Vol 16 (7) ◽  
Author(s):  
Zeeshan Rasheed
Keyword(s):  
Social Media ◽  
Strong Influence ◽  
Social Situation ◽  
Business Growth ◽  
Data Set ◽  
Twitter User ◽  
Sql Database ◽  
The World ◽  
Trending Topics ◽  
Twitter Users

Twitter has now become the most common social platform to express views on any topic. A micro-blogging social media offers a way for people around the world to show their sentiments about any political, social and cultural subject of the time. In this paper, the sentimental analysis approach has been used to analyze the positive and negative sentiments of Twitter users about some top trending #tags around the globe. The data has been collected between the duration of March to April 2021. The collected data were processed by using the Python program and then transformed our data set with the help of the SQL database. We have used graphs and tables to present the data, collected under three hashtags; which were top trending topics on that particular era. The tweets were elaborated by positive, negative and neutral sentiments which were depicted in graphs. It is clear from the results and comparison that social media has a strong influence in the present era and can be highly helpful to use as a predictor of any political, social situation prevailing in any country or worldwide. It has also been helpful for business communities to analyze their products in the same manner to improve their business growth.

scholarly journals Diagnosis and Management of Allergic Rhinitis in Children

2020 ◽  
Vol 5 (2) ◽  
pp. 159
Author(s):  
Kavinda Dayasiri ◽  
V Thadchanamoorthy ◽  
Umasunthar Thisanayagam
Keyword(s):  
Allergic Rhinitis ◽  
Negative Impact ◽  
Severe Disease ◽  
Nasal Discharge ◽  
Line Treatment ◽  
First Line ◽  
Pharmacological Management ◽  
Oral Steroids ◽  
Non Allergic Rhinitis ◽  
First Line Treatment

Allergic rhinitis which is the most common pediatric allergic disease has a significant negative impact on quality of life in affected children. Further, overall poor control can lead to ‘allergic march’ and later development of bronchial asthma. The main symptoms of allergic rhinitis include nasal discharge, blockage and itchiness of nose, and sneezing. Clinical history focused on identification of nature and severity of symptoms, trigger factors and clinical features of non-allergic rhinitis is crucial for early and accurate diagnosis.The mainstay of non-pharmacological management of allergic rhinitis is allergen avoidance.Second-line antihistamines used either locally or orally are first-line treatment of mild to moderate allergic rhinitis whereas topical nasal corticosteroids are the first line treatment for moderate to severe disease, in whom the control of symptoms is not achieved with antihistamine and those with severe nasal obstruction.Combination therapy with antihistamines and intranasal steroids is more effective than either alone and is second line treatment for children who have poorly controlled rhinitis while on monotherapy. Oral steroids may be indicated in children with significant nasal obstruction and routine use of oral steroids should be avoided.Referral to specialist allergy clinic should be considered for those who are symptomatic despite optimal local and oral therapy. Consideration should be given for specialist otorhinolaryngologist evaluation of children who have features of non-allergic rhinitis and pharmacotherapy resistant nasal obstruction.International Journal of Human and Health Sciences Vol. 05 No. 02 April’21 Page: 159-162

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