scholarly journals Network Connections and Neighbourhood Perception: Using Social Media Postings to Capture Attitudes among Twitter Users in Estonia

2017 ◽  
Vol 13 (1) ◽  
pp. 67-78 ◽  
Author(s):  
Daniel Baldwin Hess ◽  
Evan Iacobucci ◽  
Annika Väiko

Abstract The residential landscape of a city is key to its economic, social, and cultural functioning. Following the collapse of communist rule in the countries of Central and Eastern Europe (CEE) in the late 1980s and early 1990s, urban residential dynamics and household mobility have been critical to urban change under new economies and political systems. This article explores neighbourhood perception, which is a link in the chain to better explanation of socio-spatial processes (and their interruption by the socialist system). We use a novel data set – opinions expressed on one of social media (Twitter), and a novel empirical method – neural network analysis, to explore people’s current attitudes and perceptions about the neighbourhoods and districts in Tartu, Estonia. The findings suggest that Twitter comments about urban neighbourhoods display attitudinal and perceptual commentary, which is subdued compared to other subjects. The socialist goal of homogeneity in neighbourhoods is not reflected in present day perspectives about urban neighbourhoods, 25 years after the disintegration of the USSR. Ambivalence about neighbourhoods persists, but this ambivalence may be in flux. Older, formerly neglected neighbourhoods, the subject of positive perception on social media, are currently experiencing increased investment, and the observed trends in our data support a narrative of neighbourhood transition.

Author(s):  
Kristen Weidner ◽  
Joneen Lowman ◽  
Anne Fleischer ◽  
Kyle Kosik ◽  
Peyton Goodbread ◽  
...  

Purpose Telepractice was extensively utilized during the COVID-19 pandemic. Little is known about issues experienced during the wide-scale rollout of a service delivery model that was novel to many. Social media research is a way to unobtrusively analyze public communication, including during a health crisis. We investigated the characteristics of tweets about telepractice through the lens of an established health technology implementation framework. Results can help guide efforts to support and sustain telehealth beyond the pandemic context. Method We retrieved a historical Twitter data set containing tweets about telepractice from the early months of the pandemic. Tweets were analyzed using a concurrent mixed-methods content analysis design informed by the nonadoption, abandonment, scale-up, spread, and sustainability (NASSS) framework. Results Approximately 2,200 Twitter posts were retrieved, and 820 original tweets were analyzed qualitatively. Volume of tweets about telepractice increased in the early months of the pandemic. The largest group of Twitter users tweeting about telepractice was a group of clinical professionals. Tweet content reflected many, but not all, domains of the NASSS framework. Conclusions Twitter posting about telepractice increased during the pandemic. Although many tweets represented topics expected in technology implementation, some represented phenomena were potentially unique to speech-language pathology. Certain technology implementation topics, notably sustainability, were not found in the data. Implications for future telepractice implementation and further research are discussed.


2017 ◽  
Vol 37 (1) ◽  
pp. 57-65 ◽  
Author(s):  
Chamil Rathnayake ◽  
Wayne Buente

The role of automated or semiautomated social media accounts, commonly known as “bots,” in social and political processes has gained significant scholarly attention. The current body of research discusses how bots can be designed to achieve specific purposes as well as instances of unexpected negative outcomes of such use. We suggest that the interplay between social media affordances and user practices can result in incidental effects from automated agents. We examined a Twitter network data set with 1,782 nodes and 5,640 edges to demonstrate the engagement and outreach of a retweeting bot called Siripalabot that was popular among Sri Lankan Twitter users. The bot served the simple function of retweeting tweets with hashtags #SriLanka and #lk to its follower network. However, the co-use of #Sri Lanka and/or #lk with #PresPollSL, a hashtag used to discuss politics related to Sri Lanka’s presidential election in 2015, resulted in the bot incidentally amplifying the political voice of less engaged actors. The analysis demonstrated that the bot dominated the network in terms of engagement (out-degree) and the ability to connect distant clusters of actors (betweenness centrality) while more traditional actors, such as the main election candidates and news accounts, indicated more prestige (in-degree) and power (eigenvector centrality). We suggest that the study of automated agents should include designer intentions, the design and behavior of automated agents, user expectations, as well as unintended and incidental effects of interaction.


2016 ◽  
Vol 9 (3) ◽  
pp. 165-176
Author(s):  
Tobore Igbe ◽  
Bolanle Ojokoh ◽  
Olumide Adewale

Social networking website creates new ways for engaging people belonging to different communities, moral and social values to communicate and share valuable knowledge, therefore creating a large amount of data. The importance of mining social media cannot be over emphasized, due to significant information that are revealed which can be applied in different areas. In this paper, a systematic approach for traversing the content of weblog, considering location and time (spatiotemporal) is proposed. The proposed model is capable of searching for subjects in social media using Boyer Moore Horspool (BMH) algorithm with respect to location and time. BMH is an efficient string searching algorithm, where the search is done in such a way that every character in the text needs not to be checked and some characters can be skipped without missing the subject occurrence. Semantic analysis was carried out on the subject by computing the mean occurrence of the subject with the corresponding predicate and object from the total occurrence of the subject. Experiments were carried out on two datasets: the first category was crawled from twitter website from September to October 2014 and the second category was obtained from spinn3r data set made available through the International AAAI (Association for the Advancement of Artificial Intelligence) Conference on Web and Social Media (ICWSM). The results obtained from tracking some subjects such as Islam and Obama shows that the mean occurrence of the analysis of the subject successfully reveals the pattern of the subject over a period of time for a specific location. Evaluation of the system which is based on performance and functionality reveals that the model performs better than some baseline models. The proposed model is capable of revealing spatiotemporal pattern for a subject, and can be applied in any area where spatiotemporal factor is to be considered.


Author(s):  
Zeeshan Rasheed

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.


2019 ◽  
Vol 3 (Supplement_1) ◽  
pp. S176-S176
Author(s):  
Brenna M Parker ◽  
Megan Walker ◽  
Jeanette Ross

Abstract The use of social media platforms as an educational tool to promote awareness has become increasingly popular as technology advances. Twitter is a microblogging, social media platform in which users share short, text-based posts (“tweets”) that can contain hyperlinked articles, web-pages, pictures, and more. 79% of the 336 million current monthly twitter users are international, suggesting Twitter serves as a tool allowing international connection via the rapid spread of information worldwide. Simplur Signals (Simplur LLC) was used to perform a retrospective analysis of the use of #Geriatrics on Twitter. Data was collected from Oct. 13th, 2010 through Jun. 5th, 2018. Spam and unknown accounts were excluded from the data set before analysis. Manual analysis was performed to qualitatively assess tweet content of the top 200 Retweets by Impressions. A total of 65,002 tweets were shared during the selected time frame. Tweet activity rose to a high in Year 5 (17,206) but has declined since. The majority of the top 100 influencers were doctors (57.4%). Regarding tweet content, most discussions focus on increasing awareness and promoting advocacy (30%) as well as sharing research related to the practice of geriatrics (23.5%). With its widespread use and lack of international boundaries, Twitter serves as an effective platform in informing and increasing awareness about geriatrics and other medical specialties.


2021 ◽  
Vol 3 ◽  
Author(s):  
Aengus Bridgman ◽  
Eric Merkley ◽  
Oleg Zhilin ◽  
Peter John Loewen ◽  
Taylor Owen ◽  
...  

The COVID-19 pandemic has occurred alongside a worldwide infodemic where unprecedented levels of misinformation have contributed to widespread misconceptions about the novel coronavirus. Conspiracy theories, poorly sourced medical advice, and information trivializing the virus have ignored national borders and spread quickly. This information spread has occurred despite generally strong preferences for domestic national media and social media networks that tend to be geographically bounded. How, then, is (mis)information crossing borders so rapidly? Using social media and survey data, we evaluate the extent to which consumption and propagation patterns of domestic and international traditional news and social media can help inform theorizing about cross-national information spread. In a detailed case study of Canada, we employ a large multi-wave survey and a massive data set of Canadian Twitter users. We show that the majority of misinformation circulating on Twitter that is shared by Canadian accounts is retweeted from U.S.-based accounts. Moreover, exposure to U.S.-based media outlets is associated with COVID-19 misperceptions and increased exposure to U.S.-based information on Twitter is associated with an increased likelihood to post misinformation. We thus theorize and empirically identify a key globalizing infodemic pathway: disregard for national origin of social media posting.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Syeda Hina Batool ◽  
Wasim Ahmed ◽  
Khalid Mahmood ◽  
Ashraf Sharif

Purpose The use of social media has increased during the COVID-19 pandemic. Social media platforms provide opportunities to share news, ideas and personal stories. Twitter is used by citizens in Pakistan to respond and comment on emerging news stories and events. However, it is not known whether Twitter played a positive or negative role in spreading updates and preventive messages during the COVID-19 pandemic. The purpose of this study is to analyse content from Twitter during the pandemic. Design/methodology/approach NodeXL was used to retrieve data using the keyword وائرس کورونا (written in Urdu and which translates to Coronavirus). The first data set (Case Study 1) was based on 10,284 Twitter users from the end of March. The second data set (Case Study 2) was based on 10,644 Twitter users from the start of April. The theoretical lens of effective message framing was used to classify the most retweeted content on Twitter. Findings Twitter was used for personal and professional projections and included certain tweets included political motives even during the unfolding health crisis. There appeared to be very few successful attempts to use Twitter as a tool for health awareness and risk communication. The empirical findings indicate that the most retweeted messages were gain-framed and can be classified as personal, informative and political in nature. Originality/value The present study provides insights likely to be of interest to researchers, health organizations, citizens, government and politicians that are interested in making more effective use of social media for the purposes of health promotion. The authors also provide novel insights into the key topics of discussions, websites and hashtags used by Pakistani Twitter users during the COVID-19 pandemic.


2018 ◽  
Author(s):  
Anika Oellrich ◽  
George Gkotsis ◽  
Richard James Butler Dobson ◽  
Tim JP Hubbard ◽  
Rina Dutta

BACKGROUND Dementia is a growing public health concern with approximately 50 million people affected worldwide in 2017 and this number is expected to reach more than 131 million by 2050. The toll on caregivers and relatives cannot be underestimated as dementia changes family relationships, leaves people socially isolated, and affects the finances of all those involved. OBJECTIVE The aim of this study was to explore using automated analysis (i) the age and gender of people who post to the social media forum Reddit about dementia diagnoses, (ii) the affected person and their diagnosis, (iii) relevant subreddits authors are posting to, (iv) the types of messages posted and (v) the content of these posts. METHODS We analysed Reddit posts concerning dementia diagnoses. We used a previously developed text analysis pipeline to determine attributes of the posts as well as their authors to characterise online communications about dementia diagnoses. The posts were also examined by manual curation for the diagnosis provided and the person affected. Furthermore, we investigated the communities these people engage in and assessed the contents of the posts with an automated topic gathering technique. RESULTS Our results indicate that the majority of posters in our data set are women, and it is mostly close relatives such as parents and grandparents that are mentioned. Both the communities frequented and topics gathered reflect not only the sufferer's diagnosis but also potential outcomes, e.g. hardships experienced by the caregiver. The trends observed from this dataset are consistent with findings based on qualitative review, validating the robustness of social media automated text processing. CONCLUSIONS This work demonstrates the value of social media data sources as a resource for in-depth studies of those affected by a dementia diagnosis and the potential to develop novel support systems based on their real time processing in line with the increasing digitalisation of medical care.


2020 ◽  
Author(s):  
Aleksandra Urman ◽  
Stefania Ionescu ◽  
David Garcia ◽  
Anikó Hannák

BACKGROUND Since the beginning of the COVID-19 pandemic, scientists have been willing to share their results quickly to speed up the development of potential treatments and/or a vaccine. At the same time, traditional peer-review-based publication systems are not always able to process new research promptly. This has contributed to a surge in the number of medical preprints published since January 2020. In the absence of a vaccine, preventative measures such as social distancing are most helpful in slowing the spread of COVID-19. Their effectiveness can be undermined if the public does not comply with them. Hence, public discourse can have a direct effect on the progression of the pandemic. Research shows that social media discussions on COVID-19 are driven mainly by the findings from preprints, not peer-reviewed papers, highlighting the need to examine the ways medical preprints are shared and discussed online. OBJECTIVE We examine the patterns of medRxiv preprint sharing on Twitter to establish (1) whether the number of tweets linking to medRxiv increased with the advent of the COVID-19 pandemic; (2) which medical preprints were mentioned on Twitter most often; (3) whether medRxiv sharing patterns on Twitter exhibit political partisanship; (4) whether the discourse surrounding medical preprints among Twitter users has changed throughout the pandemic. METHODS The analysis is based on tweets (n=557,405) containing links to medRxriv preprint repository that were posted between the creation of the repository in June 2019 and June 2020. The study relies on a combination of statistical techniques and text analysis methods. RESULTS Since January 2020, the number of tweets linking to medRxiv has increased drastically, peaking in April 2020 with a subsequent cool-down. Before the pandemic, preprints were shared predominantly by users we identify as medical professionals and scientists. After January 2020, other users, including politically-engaged ones, have started increasingly tweeting about medRxiv. Our findings indicate a political divide in sharing patterns of the top-10 most-tweeted preprints. All of them were shared more frequently by users who describe themselves as Republicans than by users who describe themselves as Democrats. Finally, we observe a change in the discourse around medRxiv preprints. Pre-pandemic tweets linking to them were predominantly using the word “preprint”. In February 2020 “preprint” was taken over by the word “study”. Our analysis suggests this change is at least partially driven by politically-engaged users. Widely shared medical preprints can have a direct effect on the public discourse around COVID-19, which in turn can affect the societies’ willingness to comply with preventative measures. This calls for an increased responsibility when dealing with medical preprints from all parties involved: scientists, preprint repositories, media, politicians, and social media companies. CONCLUSIONS Widely shared medical preprints can have a direct effect on the public discourse around COVID-19, which in turn can affect the societies’ willingness to comply with preventative measures. This calls for an increased responsibility when dealing with medical preprints from all parties involved: scientists, preprint repositories, media, politicians, and social media companies.


2020 ◽  
Author(s):  
Ethan Kaji ◽  
Maggie Bushman

BACKGROUND Adolescents with depression often turn to social media to express their feelings, for support, and for educational purposes. Little is known about how Reddit, a forum-based platform, compares to Twitter, a newsfeed platform, when it comes to content surrounding depression. OBJECTIVE The purpose of this study is to identify differences between Reddit and Twitter concerning how depression is discussed and represented online. METHODS A content analysis of Reddit posts and Twitter posts, using r/depression and #depression, identified signs of depression using the DSM-IV criteria. Other youth-related topics, including School, Family, and Social Activity, and the presence of medical or promotional content were also coded for. Relative frequency of each code was then compared between platforms as well as the average DSM-IV score for each platform. RESULTS A total of 102 posts were included in this study, with 53 Reddit posts and 49 Twitter posts. Findings suggest that Reddit has more content with signs of depression with 92% than Twitter with 24%. 28.3% of Reddit posts included medical content compared to Twitter with 18.4%. 53.1% of Twitter posts had promotional content while Reddit posts didn’t contain promotional content. CONCLUSIONS Users with depression seem more willing to discuss their mental health on the subreddit r/depression than on Twitter. Twitter users also use #depression with a wider variety of topics, not all of which actually involve a case of depression.


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