scholarly journals Assessing Place Type Similarities Based on Functional Signatures Extracted from Social Media Data

2021 ◽  
Vol 10 (9) ◽  
pp. 626
Author(s):  
Doori Oh ◽  
Xiaobai A. Yao
Keyword(s):  
Social Media ◽  
Analytical Approach ◽  
High Similarity ◽  
Social Media Data ◽  
Data Alignment ◽  
Twitter Data ◽  
Place Descriptions ◽  
Media Data ◽  
Type Classification

Place types are often used to query places or retrieve data in gazetteers. Existing gazetteers do not use the same place type classification schemes, and the various typing schemes can cause difficulties in data alignment and matching. Different place types may share some level of similarities. However, previous studies have paid little attention to the place type similarities. This study proposes an analytical approach to measuring similarities between place types in multiple typing schemes based on functional signatures extracted from web-harvested place descriptions. In this study, a functional signature consists of three component signature factors: place affordance, events, and key-descriptors. The proposed approach has been tested in a case study using Twitter data. The case study finds high similarity scores between some pairs of types and summarizes the situations when high similarities could occur. The research makes two innovative contributions: First, it proposes a new analytical approach to measuring place type similarities. Second, it demonstrates the potential and benefits of using location-based social media data to better understand places.

scholarly journals What Your Tweets Tell Us About You: Identity, Ownership and Privacy of Twitter Data

2012 ◽  
Vol 7 (1) ◽  
pp. 174-197 ◽  
Author(s):  
Heather Small ◽  
Kristine Kasianovitz ◽  
Ronald Blanford ◽  
Ina Celaya
Keyword(s):  
Social Media ◽  
Social Networking Sites ◽  
Data Sets ◽  
Data Set ◽  
Social Media Data ◽  
Twitter Data ◽  
Other Information ◽  
Rich Data ◽  
Additional Value ◽  
Media Data

Social networking sites and other social media have enabled new forms of collaborative communication and participation for users, and created additional value as rich data sets for research. Research based on accessing, mining, and analyzing social media data has risen steadily over the last several years and is increasingly multidisciplinary; researchers from the social sciences, humanities, computer science and other domains have used social media data as the basis of their studies. The broad use of this form of data has implications for how curators address preservation, access and reuse for an audience with divergent disciplinary norms related to privacy, ownership, authenticity and reliability.In this paper, we explore how the characteristics of the Twitter platform, coupled with an ambiguous and evolving understanding of privacy in networked communication, and divergent disciplinary understandings of the resulting data, combine to create complex issues for curators trying to ensure broad-based and ethical reuse of Twitter data. We provide a case study of a specific data set to illustrate how data curators can engage with the topics and questions raised in the paper. While some initial suggestions are offered to librarians and other information professionals who are beginning to receive social media data from researchers, our larger goal is to stimulate discussion and prompt additional research on the curation and preservation of social media data.

Changing Trends in Long-Term Sentiments and Neighborhood Determinants in a Shrinking City

2021 ◽  
pp. 0739456X2110442
Author(s):  
Yunmi Park ◽  
Minju Kim ◽  
Jiyeon Shin ◽  
Megan E. Heim LaFrombois
Keyword(s):  
Social Media ◽  
Built Environment ◽  
Urban Regeneration ◽  
Neighborhood Conditions ◽  
Social Media Data ◽  
Twitter Data ◽  
Changing Trends ◽  
Shrinking City ◽  
Media Data

This research examined social media’s role in understanding perceptions about the spaces in which individuals interact, what planners can learn from social media data, and how to use social media to inform urban regeneration efforts. Using Twitter data from 2010 to 2018 recorded in one U.S. shrinking city, Detroit, Michigan, this paper longitudinally investigated topics that people discuss, their emotions, and neighborhood conditions associated with these topics and sentiments. Findings demonstrate that neighborhood demographics, socioeconomic, and built environment conditions impact people’s sentiments.

Discovering New Tourist Attractions Through Social Media Data: A Case Study in Sabah Malaysia

2018 ◽  
Author(s):  
Maisarah Abdul Halim ◽  
Noraain Mohamed Saraf ◽  
Nur Idzhainee Hashim ◽  
Abdul Rauf Abdul Rasam ◽  
Ahmad Norhisyam Idris ◽  
...  
Keyword(s):  
Social Media ◽  
Social Media Data ◽  
Tourist Attractions ◽  
Media Data

scholarly journals Penggunaan Aplikasi Media Sosial Berbasis Audio Visual dalam Membentuk Konsep Diri (Studi Kasus Aplikasi Tiktok)

Koneksi ◽  
2020 ◽  
Vol 4 (2) ◽  
pp. 372
Author(s):  
Dian Novita Sari Chandra Kusuma ◽  
Roswita Oktavianti
Keyword(s):  
Social Media ◽  
Uses And Gratifications ◽  
Age Groups ◽  
The Self ◽  
Self Concept ◽  
Internal Factors ◽  
Positive Direction ◽  
Social Media Data ◽  
Media Data

TikTok social media is popular with various groups and age groups. TikTok is an audio visual based social media application that contains short videos that are homemade or made by other people who entertain with interesting features such as the latest music, unique face filters and others. This study uses the Theory of Uses and Gratifications to determine individual satisfaction in using TikTok social media. Social media can shape the self-concept of its users based on internal factors (physical and psychological) and external factors (other people and reference groups). This study aims to find out how the use of audio visual-based social media in shaping the self-concept of users with different age levels. This study uses a qualitative approach with a case study method for users of TikTok social media. Data collection was carried out using observations and interviews with 4 sources of users of TikTok applications who have different age levels. The results of this study indicate differences in the age level of TikTok users affect the duration of using the application also affect the formation of self-concept formed by the speakers. The use of the TikTok application forms the self-concept of the resource person in a positive direction such as increasing the confidence of the resource person to show his identity and negative self-concepts such as lack of time management.Media sosial TikTok digemari oleh berbagai kalangan dan jenjang umur. TikTok adalah aplikasi media sosial berbasis audio visual yang berisikan video-video pendek buatan sendiri maupun buatan orang lain yang menghibur dengan fitur-fitur menarik seperti musik terbaru, filter wajah yang unik dan lain-lain. Penelitian ini menggunakan Teori Uses and Gratifications untuk mengetahui kepuasan individu dalam menggunakan media sosial TikTok. Media sosial dapat membentuk konsep diri dari penggunanya berdasarkan faktor internal (fisik dan psikis) dan faktor eksternal (orang lain dan kelompok rujukan). Penelitian ini bertujuan untuk mengetahui bagaimana penggunaan media sosial berbasis audio visual dalam membentuk konsep diri penggunanya dengan jenjang umur yang berbeda. Penelitian ini menggunakan pendekatan kualitatif dengan metode studi kasus terhadap pengguna media sosial TikTok. Pengumpulan data dilakukan menggunakan observasi dan wawancara kepada 4 narasumber pengguna aplikasi TikTok yang memiliki jenjang umur yang berbeda. Hasil dari penelitian ini menunjukkan perbedaan jenjang umur pengguna TikTok mempengaruhi durasi dalam menggunakan aplikasi juga mempengaruhi pembentukan konsep diri yang dibentuk oleh narasumber. Penggunaan aplikasi TikTok membentuk konsep diri narasumber ke arah positif seperti meningkatkan kepercayaan diri narasumber untuk menunjukkan jati dirinya dan konsep diri negatif seperti kurangnya dalam mengatur waktu.

scholarly journals A Comprehensive Analysis of Approaches for Sentiment Analysis Using Twitter Data on COVID-19 Vaccines

2021 ◽  
Vol 2 (2) ◽  
pp. 1-10
Author(s):  
Amrita Mishra ◽  
Keyword(s):  
Machine Learning ◽  
Social Media ◽  
Sentiment Analysis ◽  
Text Classification ◽  
Comprehensive Analysis ◽  
Social Media Data ◽  
The Public ◽  
Opinion Analysis ◽  
Twitter Data ◽  
Media Data

Sentiment Analysis has paved routes for opinion analysis of masses over unrestricted territorial limits. With the advent and growth of social media like Twitter, Facebook, WhatsApp, Snapchat in today’s world, stakeholders and the public often takes to expressing their opinion on them and drawing conclusions. While these social media data are extremely informative and well connected, the major challenge lies in incorporating efficient Text Classification strategies which not only overcomes the unstructured and humongous nature of data but also generates correct polarity of opinions (i.e. positive, negative, and neutral). This paper is a thorough effort to provide a brief study about various approaches to SA including Machine Learning, Lexicon Based, and Automatic Approaches. The paper also highlights the comparison of positive, negative, and neutral tweets of the Sputnik V, Moderna, and Covaxin vaccines used for preventive and emergency use of COVID-19 disease.

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