scholarly journals Strategic Sustainable Development Through the Lenses of Tourists’ Preferences: A Geotagged Photo Approach

2019 ◽  
Vol 12 (3) ◽  
pp. 12
Author(s):  
Zhihua Zhang ◽  
Rachel J. C. Chen ◽  
Lee D. Han
Keyword(s):  
Sustainable Development ◽  
National Parks ◽  
National Park ◽  
Spatial And Temporal Patterns ◽  
Social Media Data ◽  
Great Smoky Mountains ◽  
Data Source ◽  
Geotagged Photos ◽  
Geotagged Photo ◽  
Media Data

Knowing tourists’ preferences and experiences with respect to their national park visits is of great importance to implementing strategically sustainable development of national parks. Flickr geotagged photos are utilized and analyzed as our main data source. We included 7090 photos from 626 people in the Great Smoky Mountains National Park to investigate visitors’ behaviors through the presentations of photo spatial and temporal patterns. The results indicated that tourist behaviors that reflect on what they like and enjoy during their park visits can be extracted from geotagged social media data in terms of frequency and length of enjoyment as visitors’ preferred spots.

scholarly journals Using social media data to map the areas most affected by ISIS in Syria

2020 ◽  
Vol 26 (1) ◽  
pp. 464-470
Author(s):  
Mohamad Hasan
Keyword(s):  
Social Media ◽  
Language Processing ◽  
Geographical Information ◽  
Data Mapping ◽  
Islamic State ◽  
Social Media Data ◽  
The Social ◽  
Mapping Process ◽  
Data Source ◽  
Media Data

This paper presents a model to collect, save, geocode, and analyze social media data. The model is used to collect and process the social media data concerned with the ISIS terrorist group (the Islamic State in Iraq and Syria), and to map the areas in Syria most affected by ISIS accordingly to the social media data. Mapping process is assumed automated compilation of a density map for the geocoded tweets. Data mined from social media (e.g., Twitter and Facebook) is recognized as dynamic and easily accessible resources that can be used as a data source in spatial analysis and geographical information system. Social media data can be represented as a topic data and geocoding data basing on the text of the mined from social media and processed using Natural Language Processing (NLP) methods. NLP is a subdomain of artificial intelligence concerned with the programming computers to analyze natural human language and texts. NLP allows identifying words used as an initial data by developed geocoding algorithm. In this study, identifying the needed words using NLP was done using two corpora. First corpus contained the names of populated places in Syria. The second corpus was composed in result of statistical analysis of the number of tweets and picking the words that have a location meaning (i.e., schools, temples, etc.). After identifying the words, the algorithm used Google Maps geocoding API in order to obtain the coordinates for posts.

scholarly journals EXTRACTING AND COMPARING PLACES USING GEO-SOCIAL MEDIA

2015 ◽  
Vol II-3/W5 ◽  
pp. 311-316
Author(s):  
F. O. Ostermann ◽  
H. Huang ◽  
G. Andrienko ◽  
N. Andrienko ◽  
C. Capineri ◽  
...  
Keyword(s):  
Social Media ◽  
Semantic Similarity ◽  
Data Set ◽  
Social Media Data ◽  
Temporal Clustering ◽  
Depth Study ◽  
Data Source ◽  
Spatio Temporal ◽  
Media Data

Increasing availability of Geo-Social Media (e.g. Facebook, Foursquare and Flickr) has led to the accumulation of large volumes of social media data. These data, especially geotagged ones, contain information about perception of and experiences in various environments. Harnessing these data can be used to provide a better understanding of the semantics of places. We are interested in the similarities or differences between different Geo-Social Media in the description of places. This extended abstract presents the results of a first step towards a more in-depth study of semantic similarity of places. Particularly, we took places extracted through spatio-temporal clustering from one data source (Twitter) and examined whether their structure is reflected semantically in another data set (Flickr). Based on that, we analyse how the semantic similarity between places varies over space and scale, and how Tobler's first law of geography holds with regards to scale and places.

scholarly journals Distant Supervision for Mental Health Management in Social Media: Suicide Risk Classification System Development Study

10.2196/26119 ◽  
2021 ◽  
Vol 23 (8) ◽  
pp. e26119
Author(s):  
Guanghui Fu ◽  
Changwei Song ◽  
Jianqiang Li ◽  
Yue Ma ◽  
Pan Chen ◽  
...  
Keyword(s):  
Social Media ◽  
Suicide Risk ◽  
Health Management ◽  
System Development ◽  
Common People ◽  
Web Based ◽  
Social Media Data ◽  
Distant Supervision ◽  
Data Source ◽  
Media Data

Background Web-based social media provides common people with a platform to express their emotions conveniently and anonymously. There have been nearly 2 million messages in a particular Chinese social media data source, and several thousands more are generated each day. Therefore, it has become impossible to analyze these messages manually. However, these messages have been identified as an important data source for the prevention of suicide related to depression disorder. Objective We proposed in this paper a distant supervision approach to developing a system that can automatically identify textual comments that are indicative of a high suicide risk. Methods To avoid expensive manual data annotations, we used a knowledge graph method to produce approximate annotations for distant supervision, which provided a basis for a deep learning architecture that was built and refined by interactions with psychology experts. There were three annotation levels, as follows: free annotations (zero cost), easy annotations (by psychology students), and hard annotations (by psychology experts). Results Our system was evaluated accordingly and showed that its performance at each level was promising. By combining our system with several important psychology features from user blogs, we obtained a precision of 80.75%, a recall of 75.41%, and an F1 score of 77.98% for the hardest test data. Conclusions In this paper, we proposed a distant supervision approach to develop an automatic system that can classify high and low suicide risk based on social media comments. The model can therefore provide volunteers with early warnings to prevent social media users from committing suicide.

scholarly journals NATIONAL PARK AS THE ELEMENT OF RESOURCE SECURITY OF THE PROCESS OF ACHIEVING SUSTAINABLE SOCIAL AND ECONOMIC DEVELOPMENT OF THE REGION

2018 ◽  
pp. 39-47
Author(s):  
Nataliya Sergeevna Kholodkovskaya
Keyword(s):  
Sustainable Development ◽  
Development Strategy ◽  
National Parks ◽  
National Park ◽  
Economic Restructuring ◽  
Environmental Indicators ◽  
Entire Area ◽  
Surrounding Areas ◽  
The Impact ◽  
Recreational Resources

The long-term strategic goal of Russia is the sustainable development of its regions. Recreational resources are able to create conditions for sustainable development of the region, the importance of which is due to the fact that on the one hand they are the basis and source of economic restructuring and its modernization, and on the other, they have an impact on social factors of sustainable development. National parks, being one of the important forms of natural and recreational resources, can become the initiators and centers of active dissemination of sustainable development strategy in the surrounding areas. The paper studies the impact of alternative use of the potential of national parks in the formation of sustainable development of the region. As a factorial feature, the share of the area of the national Park in the region of its location from the entire area of the region was made, as a result - indicators corresponding to the economic, social and environmental spheres of sustainable development of the region. The indicators of the resulting indicators of the economic sphere of development of the region were selected: GRP per capita, investment in fixed capital aimed at protecting the environment and the rational use of natural resources; current costs of environmental protection; social - morbidity rates per 1.000 people, the number of deaths per 1.000 people; life expectancy; environmental - the number of air samples studied exceeding the maximum allowable concentration as a percentage of the total number of samples studied. To measure the tightness of the relationship between certain indicators, the calculation of the empirical correlation ratio was applied. The calculations show the existence of links between the size of the national Park and economic, social and environmental indicators, thereby confirming the special functional role of recreational resources in the formation of the foundations of sustainable development of the region, which should now be considered as the basis and source of economic restructuring and modernization.

Studies of depression and anxiety using Reddit as a data source: Scoping review (Preprint)

2021 ◽  
Author(s):  
Nick Boettcher
Keyword(s):  
Mental Health ◽  
Social Media ◽  
Scoping Review ◽  
Primary Data ◽  
Technical Solution ◽  
Depression And Anxiety ◽  
Social Media Data ◽  
Primary Data Source ◽  
Data Source ◽  
Media Data

BACKGROUND The study of depression and anxiety using publicly available social media data is a research activity that has grown considerably over the last decade. The discussion platform Reddit has become a popular social media data source in this nascent area of study, in part because of the unique ways in which the platform is facilitative of research. To date, no work has been done to synthesize existing studies of depression and anxiety using Reddit. OBJECTIVE The objective of this review is to understand the scope and nature of research using Reddit as a primary data source for studying depression and anxiety. METHODS A scoping review was conducted using the Arksey and O’Malley framework. Academic databases searched include MEDLINE/PubMed, EMBASE, CINAHL, PsycINFO, PsycARTICLES, Scopus, ScienceDirect, IEEE Xplore, and ACM database. Inclusion criteria were developed using the Participants/Concept/Context framework outlined by the Joanna Briggs Institute Scoping Review Methodology Group. Eligible studies featured a methodological focus on analyzing depression and/or anxiety using naturalistic written expressions from Reddit users as the primary data source. RESULTS 54 Studies were included for review. Tables and corresponding analysis delineate key methodological features including a comparatively larger focus on depression versus anxiety, an even split of original and premade datasets, a favored analytic focus on classifying the mental health states of Reddit users, and practical implications often recommending new methods of professionally-driven mental health monitoring and outreach for Reddit users. CONCLUSIONS Studies of depression and anxiety using Reddit data are currently driven by a prevailing methodology which favors a technical, solution-based orientation. Researchers interested in advancing this research area will benefit from further consideration of conceptual issues surrounding interpretation of Reddit data with the medical model of mental health. Further efforts are also needed to locate accountability and autonomy within practice implications suggesting new forms of engagement with Reddit users.

scholarly journals Successes and Challenge in Sustainable Development Goals Localisation for Host Communities around Kruger National Park

2021 ◽  
Vol 13 (10) ◽  
pp. 5341
Author(s):  
Mashudu Andra Mabibibi ◽  
Kaitano Dube ◽  
Konanani Thwala
Keyword(s):  
Sustainable Development ◽  
National Parks ◽  
National Park ◽  
Sustainable Development Goals ◽  
Kruger National Park ◽  
Host Community ◽  
The Sustainable Development ◽  
Development Goals ◽  
Tourism Enterprises ◽  
Sustainability Challenges

Tourism has often been blamed for its unsustainable ways for a number of years now. Consequently, there have been efforts to ensure that tourism contributes to the host communities to address some of the sustainability challenges through responsible and sustainable tourism initiatives in the recent past. With less than nine years to go before the lapse of the Sustainable Development Goals (SDGs), there is a need to take stock of how tourism enterprises such as national parks are contributing to the SDGs. This study examines how Kruger National Parks (KNP) is assisting the host communities in meeting the SDG goals and targets. The study made use of 30 in-depth key informant interviews, field observations and critical document analysis. The study found that regardless of the challenges it faces as an organization in partnering with host communities for developmental purposes, Kruger National Park has assisted communities to meet at least 15 out of the 17 SDGs. These span from social to economic, environmental and cultural SDGs. Since KNP’s projects address host community needs, several challenges need to be dealt with to ensure the sustainability of these projects post COVID-19 pandemic, which has undermined many nature tourism establishments worldwide. Besides the pandemic, there is a need to manage community expectations with regard to how far it can address some of the challenges faced by communities.

scholarly journals REALISASI TINDAK KESANTUNAN POSITIF DALAM WACANA AKADEMIK DI MEDIA SOSIAL BERPERSPEKTIF HUMANIS/POSITIVE POLITENESS OF ACADEMIC DISCOURSE TAKING PLACE IN SOCIAL MEDIA INTERACTION: A HUMANITY PERSPECTIVE

Aksara ◽  
2021 ◽  
Vol 32 (2) ◽  
pp. 323-338
Author(s):  
Hari Kusmanto ◽  
Nadia Puji Ayu ◽  
Harun Joko Prayitno ◽  
Laili Etika Rahmawati ◽  
Dini Restiyanti Pratiwi ◽  
...  
Keyword(s):  
Social Media ◽  
Academic Discourse ◽  
Human Values ◽  
Social Media Data ◽  
Positive Communication ◽  
Media Interaction ◽  
Data Source ◽  
High Attitude ◽  
Equivalent Method ◽  
Media Data

Abstrak Studi ini bertujuan mendeskripsikan wujud kesantunan berkomunikasi dalam media sosial WhatsApp antara mahasiswa dan dosen. Studi ini adalah kualitatif. Data dalam studi ini adalah kalimat-kalimat santun dalam wacana akademik di media sosial. Sumber data dalam studi ini adalah tuturan wacana akademik di media sosial. Pengumpulan data dalam studi ini menggunakan metode dokumentasi, simak, dan dilanjutkan dengan teknik catat. Analisis data dalam studi ini dilakukan dengan metode padan intralingual; padan pragmatis dan diperkuat dengan teknik analisis kesantunan Brown dan Levinson berperspektif humanis. Hasil studi ini menunjukkan tindak kesantunan positif meliputi: (1) mengucapkan terima kasih sebagai penghormatan kepada mitra tutur, 48%; (2) memberikan pertanyaan sebagai wujud perhatian kepada mitra tutur, 8%; (3) memberikan informasi kepada mitra tutur sebagai wujud kepedulian, 18%; (4) menunjukkan keoptimisan kepada mitra tutur supaya termotivasi, 4%; (5) memberikan hadiah kepada mitra tutur dengan memberikan dukungan, 4%; (6) mengucapkan salam kepada mitra tutur sebagai upaya mendoakan kebaikan kepada mitra tutur, 8%; dan (7) menggunakan penanda identitas sebagai wujud menjalin solidaritas antara penutur dan mitra tutur, 10%. Hal ini menunjukkan mahasiswa memiliki sikap penghormatan yang tinggi kepada dosen dengan menunjukkan komunikasi bernada positif. Tindak kesantunan mengucapkan terima kasih, memberikan informasi yang dibutuhkan mitra tutur, menunjukkan sikap percaya diri, mengucapkan salam merupakan wujud komunikasi yang berperspektif humanis, yakni menjunjung nilai-nilai kemanusian. Penelitian ini bermanfaat dalam membangun komunikasi pembelajaran yang berorientasi pada kesantunan berbahasa yang memartabatkan nilai-nilai humanitas dalam pembelajaran. Kata kunci: kesantunan positif, akademik, media sosial, humanis Abstract This study aims to describe the form of politeness in communicating on WhatsApp social media between students and lecturers. This study is qualitative. The data in this study are polite sentences in academic discourse on social media. The data source in this study is the speech of academic discourse on social media. Data collection in this study uses the documentation method, refer to it, and proceed with note taking technique. Data analysis in this study was carried out using the intralingual equivalent method; pragmatic equivalent and strengthened by Brown and Levinson’s politeness analysis techniques with a sweet perspective. The results of this study show positive politeness actions include: (1) Thank you for the speech partner observer 48%; (2) giving questions as a form of attention to the speech partners 8%; (3) providing information to the speech partners as a form of concern 18%; (4) showing optimism for the speech partners to be motivated 4%; (5) giving gifts to speech partners by giving support 4%; (6) greeting the speech partners in an effort to pray for the kindness of the speech partners 8%; and (7) using identity markers as a form of establishing solidarity between the speaker and the speech partner 10%.. ISSN 0854-3283 (Print), ISSN 2580-0353 (Online) , Vol. 32, No. 2, Desember 2020 323 Realisasi Tindak Kesantunan Positif dalam Wacana Akademik di Media Sosial Berperspektif Humanitas Halaman 323 — 338 (Hari Kusmanto, Nadia P. Ayu, Harun J. Prayitno, Laili E. Rahmawati, Dini R. Pratiwi, dan Tri Santoso) This shows students have a high attitude of respect for lecturers by showing positive communication. Actions of thanksgiving, giving information needed by the speech partner, showing self-con dence, greeting is a form of communication with a humanist perspective, namely upholding human values. This research is useful in building learning communication that is oriented towards language politeness that digni es human values in learning. Keywords: positive politeness, academic, social media, humanity 

scholarly journals Social media as a big public health data source: review of the international bibliography

2015 ◽  
Author(s):  
Evika Karamagioli
Keyword(s):  
Public Health ◽  
Social Media ◽  
Big Data ◽  
Data Extraction ◽  
Online Communication ◽  
World Health ◽  
Health Crisis ◽  
Social Media Data ◽  
Data Source ◽  
Media Data

Background: As the use of social media creates huge amounts of data, the need for big data analysis has to synthesize the information and determine which actions is generated. Online communication channels such as Facebook, Twitter, Instagram etc provide a wealth of passively collected data that may be mined for public health purposes such as health surveillance, health crisis management, and last but not least health promotion and education. Objective: We explore international bibliography on the potential role and perceptive of use for social media as a big data source for public health purposes. Method: Systematic literature review. Data extraction and synthesis was performed with the use of thematic analysis. Results: Examples of those currently collecting and analyzing big data from generated social content include scientists who are working with the Centers for Disease Control and Prevention to track the spread of flu by analyzing what user searches, and the World Health Organization is working on disaster management relief. But what exactly do we do with this big social media data? We can track real-time trends and understand them quicker through the platforms and processing services. By processing this big social media data, it is possible to determine specific patterns in conversation topics, users behaviors, overall trends and influencers, sociodemographic characteristics, lifestyle behaviors, and social and cultural constructs. Conclusion: The key to fostering big data and social media converge is process and analyze the right data that may be mined for purposes of public health, so as to provide strategic insights for planning, execution and measurement of effective and efficient public health interventions. In this effort, political, economic and legal obstacles need to be seriously considered.

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