scholarly journals Emojis as Contextual Indicants in Location-Based Social Media Posts

2021 ◽  
Vol 10 (6) ◽  
pp. 407
Author(s):  
Eva Hauthal ◽  
Alexander Dunkel ◽  
Dirk Burghardt
Keyword(s):  
Social Media ◽  
Sentiment Analysis ◽  
Surrounding Environment ◽  
The Relationship ◽  
User Activities

The presented study aims to investigate the relationship between the use of emojis in location-based social media and the location of the corresponding post in terms of perceived objects and conducted activities connected to this place. The basis for this is not a purely frequency-based assessment, but a specifically introduced measure called typicality. To evaluate the typicality measure and examine the assumption that emojis are contextual indicants, a dataset of worldwide geotagged posts from Instagram relating to sunset and sunrise events is used, converted to a privacy-aware version based on a Hyperloglog approach. Results suggest that emojis can often provide more nuanced information about user activities and the surrounding environment than is possible with hashtags. Thus, emojis may be suitable for identifying less obvious characteristics and the sense of a place. Emojis are already explored in research, but mainly for sentiment analysis, for semantic studies or as part of emoji prediction. In contrast, this work provides novel insights into the user’s spatial or activity context by applying the typicality measure and therefore considers emojis contextual indicants.

scholarly journals A Sentiment Analysis of Twitter Content as a Predictor of Exchange Rate Movements

2015 ◽  
Vol 6 (2) ◽  
pp. 132-140
Author(s):  
Serda Selin Ozturk ◽  
Kursad Ciftci
Keyword(s):  
Social Media ◽  
Exchange Rate ◽  
Sentiment Analysis ◽  
Exchange Rate Movements ◽  
The Relationship

Recently, social media, particularly microblogs, have become highly valuableinformation resources for many investors. Previous studies examined general stockmarket movements, whereas in this paper, USD/TRY currency movements based on thechange in the number of positive, negative and neutral tweets are analyzed. Weinvestigate the relationship between Twitter content categorized as sentiments, such asBuy, Sell and Neutral, with USD/TRY currency movements. The results suggest thatthere exists a relationship between the number of tweets and the change in USD/TRYexchange rate.

scholarly journals A Corpus-Driven Approach to Sentiment Analysis of Patient Narratives

10.29007/rs9b ◽  
2018 ◽  
Author(s):  
Keith Stuart ◽  
Ana Botella ◽  
Imma Ferri-Miralles
Keyword(s):  
Health Care ◽  
Social Media ◽  
Sentiment Analysis ◽  
Patient Feedback ◽  
Patient Narratives ◽  
Growing Body ◽  
Rich Data ◽  
The Uk ◽  
The Relationship ◽  
Clinical Domain

This paper describes the linguistic analysis of a corpus of patient narratives that was used to develop and test software to carry out sentiment analysis on the aforementioned corpus. There is a growing body of research on the relationship between sentiment analysis, social media (for example, Twitter) and health care, but less research on sentiment analysis of patient narratives (being longer and more complex texts). The motivation for this research is that patient narratives of experiences of the National Health Service (NHS) in the UK provide rich data of the treatment received.The corpus threw up some unexpected results that may be of benefit for researchers of sentiment analysis. The linguistic problems encountered have been divided into three sections: the noisy nature of large corpora; the idiomatic nature of language; the nature of language in the clinical domain. This article gives an overview of the project and describes the linguistic problems that arose out of the project, which tried to find a means to automate the analysis of patient feedback on health services.

scholarly journals Analisis Sentimen Bahasa Indonesia pada Twitter Menggunakan Struktur Tree Berbasis Leksikon

2021 ◽  
Vol 8 (1) ◽  
pp. 135
Author(s):  
Feby Tri Saputra ◽  
Yani Nurhadryani ◽  
Sony Hartono Wijaya ◽  
Defina Defina
Keyword(s):  
Social Media ◽  
Standard Deviation ◽  
Sentiment Analysis ◽  
Presidential Election ◽  
Small Difference ◽  
Tree Structure ◽  
Positive Class ◽  
The Relationship ◽  
Tree Method ◽  
Bahasa Indonesia

<p class="Body">Jumlah opini di media sosial seperti Twitter tersebar luas sehingga tidak mungkin membaca semua opini untuk mendapatkan seluruh sentimen. Analisis sentimen merupakan salah satu metode untuk mengatasi masalah tersebut. Salah satu pendekatan dalam analisis sentimen adalah berbasis leksikon. Pendekatan berbasis leksikon dapat menghasilkan performa yang baik pada lintas topik pembicaraan tanpa memerlukan pelatihan data. Namun, pendekatan berbasis leksikon sangat bergantung pada kelengkapan dan keragaman sentimen leksikon. Selain itu, hubungan antarkata sangat penting untuk diperhatikan karena dapat mengubah polaritas sentimen pada teks. Hubungan antarkata dapat direpresentasikan dengan baik menggunakan struktur <em>tree</em>. Penelitian ini menggunakan struktur <em>tree</em> sebagai interpretasi hubungan antarkata dalam pembentukan kalimat dengan menambahan kata ke dalam sentimen leksikon. Metode berbasis <em>tree</em> diujikan pada data dengan lintas topik seperti data twit Pilgub Jabar 2018, Pilpres 2019, dan pandemik COVID-19. Ketiga data uji memiliki proporsi kelas yang tidak seimbang, dengan kelas terbanyak merupakan kelas positif. Metode berbasis <em>tree</em> menghasilkan akurasi sebesar 64,97% (meningkat 1,26%) pada data Pilgub Jabar 2018, 64,33% (meningkat 11,41%) pada data Pilpres 2019, dan 66,24% (meningkat 7,61%) pada data pandemik COVID-19. Metode berbasis <em>tree</em> dapat menghasilkan akurasi yang stabil pada beberapa lintas topik dibuktikan dengan standar deviasi akurasi yang kecil (0,97%) bahkan lebih kecil dari metode tanpa <em>tree </em>(5,4%). Metode berbasis <em>tree </em>dapat meningkatkan <em>weighted f1-measure</em> pada data Pilpres 2019 sebesar 10,45% dan data pandemik COVID-19 sebesar 8,1%, sedangkan hasil pada data Pilgub 2018 tidak berbeda secara signifikan. Hasil akurasi dan <em>weighted f1-measure</em> memiliki selisih yang kecil sehingga pengukuran akurasi valid dan tidak bias terhadap data tidak seimbang.</p><p class="Body"> </p><p class="Body"><em><strong>Abstract</strong></em></p><p class="Judul2"><em>The number of opinions on social media like Twitter is so widespread that it's impossible to read all those opinions to get all the sentiments. Sentiment analysis is one of the methods that could overcome this problem. The lexicon-based approach is one of the sentiment analysis approaches which perform well across data topics without training. However, the lexicon-based approach relies heavily on the completeness and diversity of sentiment lexicons. The relationship between words is important because it could change the sentiment polarity in the text. The tree structure could represent the relationship between words well. This study uses a tree structure as an interpretation of the relationship between words in a sentence. The tree structure is constructed by adding words to the lexicon sentiment. The tree-based method is tested on cross-topic data such as the tweet data of the 2018 West Java Governor Election, the 2019 Presidential Election, and the COVID-19 pandemic. All data used has an unbalanced class proportion, with the positive class being dominant. The accuracy results of the tree-based method on all data consecutively are 64.97% (increased by 1.26%), 64.33% (increased by 11.41%), and 66.24% (increased by 7.61%). The tree-based method produce stable accuracy on several topics proved by the small accuracies standard deviation (0.97%) that even smaller than the non-tree method (5.4%). The weighted f1-measure increases of the tree-based method on all data consecutively are 0% (equal), 10.45%, and 8.1%. The small difference between the weighted f1-measure and accuracy concludes that the accuracy resulted is valid.</em></p><p class="Body"><em><strong><br /></strong></em></p>

scholarly journals Money Often Costs Too Much: A Study to Investigate The Effect Of Twitter Sentiment On Bitcoin Price Fluctuation

2020 ◽  
Author(s):  
Mitul Verma ◽  
Pritish Sharma
Keyword(s):  
Social Media ◽  
Sentiment Analysis ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Svm Classifier ◽  
Price Fluctuation ◽  
Financial Investment ◽  
Digital Currency ◽  
Social Media Platforms ◽  
The Relationship

Introduced in 2009, Bitcoin has demonstrated a huge potential as the world&rsquo;s first digital currency and has been widely used as a financial investment. Our research aims to uncover the relationship between Bitcoin prices and people&rsquo;s sentiments about Bitcoin on social media. Among various social media platforms, micro-blogging is one of the most popular. Millions of people use micro-blogging platforms to exchange ideas, broadcast views, and to provide opinions on different topics related to politics, culture, science, and technology. This makes them a potentially rich source of data for sentiment analysis. Therefore we chose one of the busiest micro-blogging platforms, Twitter, to perform sentiment analysis on Bitcoin. We used ELMo embedding model to convert Bitcoin-related tweets into a vector form and SVM classifier to divide the tweets into three sentiment categories - positive, negative, and neutral. We then used the sentiment data to find its relation with Bitcoin price fluctuation using the linear mixed model.

How significant are users’ opinions in social media?

2014 ◽  
Vol 22 (4) ◽  
pp. 254-272 ◽  
Author(s):  
Hamid Khobzi ◽  
Babak Teimourpour
Keyword(s):  
Social Media ◽  
Sentiment Analysis ◽  
Social Networking Sites ◽  
Design Methodology ◽  
Regression Method ◽  
Analysis Approach ◽  
Content Type ◽  
Polarity Score ◽  
Facebook Pages ◽  
The Relationship

Purpose – The purpose of this study is to assign polarity score to each post from Facebook fan pages, and then examine whether the Comments submitted by users on a post from fan page have a significant relationship with the popularity of that post. Being aware of how to enhance the popularity of posts will help companies in terms of administrating their fan pages. Design/methodology/approach – In the context of fan page and post popularity, the authors test significance of the relationship between Comments’ polarity and number of Likes and Comments of a post in different Facebook pages by regression method. The data are collected from different fan page posts in Facebook, and a sentiment analysis approach is proposed to accomplish this research. Findings – Results show that the relation between users’ Comments and popularity of fan page posts is strongly significant. Outcomes of this research are useful for every company in terms of monitoring and managing their brand fan pages on social networking sites such as Facebook. Originality/value – Investigation of factors influencing popularity of fan page posts in social media is almost a new area of study that dates back to recent years. The authors use a sentiment analysis approach to evaluate a new concept describing the relationship between users’ Comments and popularity of posts from Facebook fan pages. Moreover, a part of dataset is extracted from Facebook by a crawler which is an advantage to prior studies.

PROSPEK USAHA INOVASI SPEAKER DAN PAJANGAN UNIK UPAYA PEMANFAATAN LIMBAH GULUNGAN KERTAS

2019 ◽  
Vol 2 (2) ◽  
pp. 171
Author(s):  
Saputri Rizki Ramadhanti ◽  
Joti Dina Kartikasari ◽  
Alfian Muttoqim Muttoqim ◽  
Umi Farida Farida ◽  
Amanda Oktaviani Amanda
Keyword(s):  
College Students ◽  
Social Media ◽  
Economic Value ◽  
Waste Paper ◽  
Direct Selling ◽  
Paper Waste ◽  
Entrepreneurial Spirit ◽  
Surrounding Environment ◽  
Business Opportunities ◽  
New Business

The amount of paper waste, especially paper waste of yarn rolls in the socks manufactured factory and the convection industry that has not been used to get high economic value is an opportunity to open a new business, especially in the electronic and art craft product. SEPIK PANIK (Speaker of Music and Unique Display of Waste Paper Rolls) is an innovation from processing paper waste to be a unique speaker. The purposes of this program are: 1) Utilizing paper waste to get high selling value. 2) Creating handmade products from paper waste into speakers as well as unique creative display. 3) To accommodate the desire of college students who have entrepreneurial spirit and artistic creations to open new business opportunities. The method of make this SEPIK PANIK product includes 1) Making paper tube of speaker and 2) Making a Unique Display. The Sales of this product have been carried out during May to August 2019, products that have been sold are 34 units, obtained a profit of Rp. 1.170,000. Sales and promotion methods are carried out both online through social media and offline, namely direct selling and consignment. Based on these results, this business is very profitable and can benefit the surrounding environment.

Analisis Pengaruh Interactivity Dan Sincerity Pada Social Mediaaccount Musisi Terhadap Sense Of Closeness Dan Reciprocity Antara Musisi Dengan Fans dan Implikasinya Terhadap Legal Purchase Intent Telaah Pada Social Media Account Instagram @Duadrum

2018 ◽  
Vol 9 (2) ◽  
pp. 49-61
Author(s):  
Moses Natadirja
Keyword(s):  
Social Media ◽  
Purchase Intention ◽  
Positive Relationship ◽  
Structural Model ◽  
Distribution Channel ◽  
Online Questionnaire ◽  
Channel One ◽  
Limited Budget ◽  
Marketing Social ◽  
The Relationship

Social media nowadays can be used not only for interacting with each other, exchanges ideas, and develop new friends, furthermore it can be used to promote and selling products or services. It is also used for musician for sales and promotion of their CD album to their fans through social media, especially for musicians , who choose to be independent with limited budget and distribution channel. One of the musician who choose to be independent is Dua Drum. The purpose of this study is to examine the relationship between musician’s social media (Interactivity & Sincerity), the tie that fans may develop via social media (Sense of Closeness & Reciprocity), and purchase legal CD album. This Research is using a quantitative approach with gathering 127 responses through online questionnaire and analyzed using Structural Model Equation (SEM). The result of this research is there are a positive relationship between Interactivity & Sincerity with Sense of Closeness & Reciprocity, and also a positive relationship between Sense of Closeness & Reciprocity with Legal Purchase Intention of CD album. Keywords: Music, Internet Marketing, Social Media Marketing, Purchase Intention

Association between Social Media Use for Health Purpose and Depressive Symptoms: A Cross-Sectional Survey (Preprint)

2020 ◽  
Author(s):  
Hee Yun Lee ◽  
Yan Luo ◽  
Cho Rong Won ◽  
Jiyoung Lee ◽  
Jeongwon Baik
Keyword(s):  
Social Media ◽  
Depressive Symptoms ◽  
Social Networking Sites ◽  
Inverse Relationship ◽  
Age Groups ◽  
Cross Sectional Survey ◽  
Cross Sectional ◽  
Use Of Social Media ◽  
The Relationship ◽  
Health Purpose

BACKGROUND The use of social media or social networking sites (SNS) is increasing across all age groups, and one of the primary motives of using SNS is to seek health-related information. Although previous research examining the effect of SNS use on depression exist, studies regarding the effect of SNS use for health purpose on depression is limited. OBJECTIVE Our study aims to explore the relationship between SNS use for health purpose and depression across the four age groups (18-34 years old, 35-49 years old, 50-64 years old, and above 65 years old). METHODS A sample of 6,789 adults aged 18 and older was extracted from a 2017 and 2018 Health Information National Trends Survey (HINTS). Univariate and bivariate analyses to examine the association between each variable and four age groups were conducted. Multiple linear regression analyses to predict depression level among participants with use of SNS for health purpose were conducted. RESULTS SNS use for health purpose and depression were positively associated for three age groups but not for those 65 years or older (=0.13, P<0.05; =0.08, P<0.05; =0.09, P<0.05). Income and self-reported health status indicated an inverse relationship for all age groups. The relationship with marital status differed based on age group with 18 and 34 years old showing an inverse relationship (=-0.13, P<0.01) while 65 years or older showing a positive relationship (=0.06, P<0.05). Gender was positively associated among those in the 35-49 years old (=0.09, P<0.05) and 65 years or older (=0.07, P<0.05). Being Non-Hispanic White was positively associated with depression among 50-64 years old (=0.07, P<0.001) and 65 years or older (=0.08, P<0.05). CONCLUSIONS Age-tailored education on determining accurate and reliable information shared via SNS is needed to reduce depressive symptoms.

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