Hashtags Research Articles

An Exploratory Approach to SNS Hashtag as a Communication Channel: Comparison of Domestic and International Cases

THashtag marketing utilize hashtag that focuses on specific SNS channel regardless of communication characteristics, and uses hashtag to increase connectivity with other SNS and induce user’s voluntary participation through specific SNS. On the other hand, domestic hashtag marketing suggests that there are many cases where users perceive the hashtag as advertising messages led by the company rather than perceive it as two-way communication by using the hashtag as a marketing campaign form on multiple SNSs. This study is about hash tag marketing that is used as an aggressive communication strategy on SNS. The purpose of this study is to suggest the methods and implications of effective communication between companies and consumers by comparing and analyzing cases by SNS hashtag marketing type and country. To this end, this study conducted a literature study and a case study in parallel. In the literature study, previous studies related to the characteristics of SNS evolution, communication theories, and hashtag marketing were reviewed. In addition, this study compares hashtag marketing by SNS type through domestic and international case analysis and draws implications for companies to execute hashtag marketing.BR The results of this study suggest that the hashtag strategy for SNS type and the culture of the country is required for the spread of hashtag marketing at the present as the function of hashtag evolves from barcamp to chasm on SNS.

Inferring of Political Leaning from Tweets, Retweets of Indian politics

The current use of on-line social networks to unfold information and change opinions, by using most of the people, news media and political actors alike, has implement new outlet of research in computational political science. Here The trouble of compute and inferring the political leaning of Twitter customers. We formulate political leaning inference as a convex optimization problem that consists of ideas: Twitter users generally tend to tweet and retweet constantly, and Similar Twitter users have a tendency to be retweeted through similar sets of target audience. Then take a look at our inference technique to a massive dataset of Indian political personnel’s related individual tweets amassed over a time frame. On a fixed of regularly retweeted resources, our method achieves a few percentage of accuracy and excessive rank correlation compared with manually created labels. By analyzing the political leaning of some amount regularly retweeted property, and get regular clients who retweeted them, and the hash tags utilized by those sources, our quantitative have a examine sheds slight at the political demographics of the Twitter population, and the temporal dynamics of political polarization as activities spread..

Automatic music emotion classification using hashtag graph

Music is integrated automatically in routine life of human being. It reveals emotion and harmonizes the listener sensation. Human’s present state of mind is interconnected with music. Distinguishing the human emotions on behalf of pitch, rhythm, harmony, melody and interval is a tedious process. Identification of human emotions is done by the machine learning approaches. The classification models that are used for predicting emotions are not very much efficient. To address the above mentioned problem a novel approach using hash tag graph generation is proposed for automatic emotion detection. The proposed method consists of two steps training and testing process. In this paper the proposed method is compared with support vector machines, k-nearest neighbour approach and convolution neural network in terms of accuracy, precision, recall, specificity, f-measure, geometric mean, root mean square error and computational cost. The proposed technique achieves the best performance in terms of all the evaluation parameters.

Hashtags, testimonies, and measurements: Gender violence and its interpretation

In this article, I address gender violence through the act of witnessing and speaking out by the victims. Starting from a critical comment on some arguable points raised in the recent Hau Journal forum aimed at discussing forms and claims of the #MeToo movement, I let emerge the conundrums that anthropology faces in dealing with the issue. A focus on domestic abuse as a specific form of gender violence allows me to delve into the twine of intimacy, agency and consent in the experience of the victims. I detect the specific dynamics that characterize the issue of speaking/not speaking out against violence by abused women and that underpin analytical biases. Then, I illustrate how these complexities can be found in the general assessment and measurement of gender violence as a global phenomenon. I conclude with a reflection on violence and women’s voices as an opportunity for anthropological knowledge to deal with truth telling, intimacy, and the gendered act of speaking out.

Common Sense & Pin Money: The Material Culture and Legacy of Lula Annie Butler 1909-2009

“Common Sense and Pin Money: The Material Culture and Legacy of Lula Annie Butler 1909-2009” examines local/global contexts of the late Mrs. Butler’s found quilts, her “make do” ethos, which made a way out of no way decades before recycle, re-purpose and green were hash tags. A lifelong Preston, Maryland resident and domestic worker, Mrs. Butler’s household was outfitted with quilts, tablecloths, aprons, pillows, and shopping bags she created from fabric-sample books and fabric remnants obtained from the late Mrs. Sarah Covey, her longest employer, who operated a drapery and upholstery business in Federalsburg, Maryland. Mrs. Butler’s artistic impulse-vibrant, improvisational, and individually expressive-is a thread of a rural Atlantic World continuum spanning from East Preston, Nova Scotia to Gee’s Bend, Alabama, all of which are transferences of African textile traditions. Like Harriet Ross Tubman, Mrs. Butler sold gingerbreads and quilts for income using skills she learned from her mother, Harriet Dyer Thomas, who learned from her mother Martha Adams Dyer, the earliest quilter, thus far, identified in this lineage of Eastern Shore women of Algonquin descent. Over three decades, Mrs. Butler made an unknown quantity of quilts to provide warmth for her family, friends, and fellow congregants at Mt. Calvary Methodist Church in Preston, Maryland. Nova Scotia, the Eastern Shore, and Gee’s Bend have isolative geographies. Preston and Gee’s Bend have approximately the same population but unlike the Alabama quilters’ collective and the African Nova Scotia Quilter’s Association, Mrs. Butler created her Chesapeake vernacular alone. Her strong alto voice, singing old hymns, emanated from her westward-facing bedroom on Newton Road as she sewed strips of cloth together at her teal-metal Singer sewing machine. This seer’s stitchery was a fabric scat embedded with a post-modern time line of textile arts in the United States.

Uso y funcionalidad didáctica de Twitter desde la perspectiva del estudiante universitario. Un estudio de caso en la UNED

Este artículo analiza el uso que realizan los estudiantes universitarios de Twitter y su percepción como recurso didáctico en la Educación Superior en el contexto de los estudios de Grado y Máster en la Facultad de Educación de la UNED. A través de una metodología mixta cuantitativa y cualitativa se analiza la percepción del alumnado sobre la funcionalidad didáctica en la Educación Superior. Los resultados muestran que lo estudiantes perciben el potencial educativo de Twitter en tres dimensiones: 1) “Síntesis, opinión y divulgación de la información”. 2) “Trabajo colaborativo en red” y 3) “Investigación y desarrollo curricular”. Asimismo, destacan especialmente actividades como el seguimiento de palabras o hashtags (60%), las reflexiones sobre tendencias en la red (63%) y la conformación de comunidades o grupos virtuales para realización de proyectos colaborativos (53%). Una amplia mayoría de los estudiantes consideran Twitter una herramienta beneficiosa para su desarrollo académico y social.

Privileged Authenticity in Reconstruction of Digital Encrypted Shares

Efficient message reconstruction mechanism depends on the entire partial shares received in random manner. This paper proposed a technique to ensure the authenticated accumulation of shares based on the privileged share.Threshold number of received shares inclusive of the privileged share, were being accumulated together to validate the original message. Although attaining threshold number of shares or more excluding the privileged share, it would not be possible to reconstruct the original message. Encryptional procedure has been put into the desired partial shares to confuse the evaesdroppers. Decisive parameter termed as hash tag has been extracted from the cumulative shares and bitwise checking procedure has been carried out. In first appearance of first mismatch, rests of the checking bits were ignored, as test case put under failure transaction. Different statistical tests namely floating frequency, entropy value have proved the robustness of the proposed technique. Thus, extensive experiments were conducted to evaluate the security and efficiency with better productivity.<strong> </strong>

A new big data approach for topic classification and sentiment analysis of Twitter data

Twitter is a major micro-blogging service, with millions of active users. These users use Twitter to post status messages called tweets and share their opinions using hash tags on various events. Hence, Twitter is considered a major real time streaming source and one of an effective and accurate indicator of opinions. The amount of data generated by Twitter is huge and it is difficult to scan entire data manually. This paper proposes a Hybrid Lexicon-Naive Bayesian Classifier (HL-NBC) method for sentimental analysis. In addition to that, Sentiment analysis engine is preceded by topic classification, which classifies tweets into different categories and filters irrelevant tweets. The proposed method is compared with Lexicon, Naive Bayesian classifier for uni-gram and bi-gram features. Out of the different approaches, the proposed HL-NBC method does sentiment classification in an improved way and gives accuracy of 82%, which is comparatively better than other methods. Also, the sentiment analysis is performed in a shorter time compared to traditional methods and achieves 93% improvement in processing time for larger datasets.

Corpus-based Topic Derivation and Timestamp-based Popular Hashtag Prediction in Twitter

With the use of the Internet, mobile platforms, online commerce, and social media services, the footprints of human behavior can be easily recorded in the digital world, which generates data on an extremely large scale. Twitter as a big data social network becomes one of the most important sources for capturing up-to-date events happened in the world. Deriving topics from Twitter is important for various applications, such as situation awareness, market analysis, content filtering, and recommendations. However, topic derivation with high purity in Twitter is hard to achieve because tweets are limited to 140 characters. Previous works on topic derivation in Twitter suffer from low purity. In this paper, we propose corpus-based topic derivation (CTD) approach that combines a Twitter corpus and LF-LDA, which is a text processing model to identify topics and clusters of similar hashtags. We use asymmetric topic LF-LDA to obtain better purity of topics. Compared to intJNMF, a representative related work, the purity (F-measure) of our proposed CTD increases from 5.26% (27.81%) to 11.32% (34.28%) for 20 to 100 topics. We also propose a timestamp-based popular hashtags prediction (TPHP) approach by creating trending hashtags lists (THLs), which are lists of hashtags used by many users and make use of timestamps in tweets. We use the edit distance to find the difference between consecutive THLs. Then the difference can be used to calculate volatilety to find how people react to real world events. Compared to Hybrid+, a representative related work, the mean average precision (MAP) of our TPHP increases by 19.45% (week-day), 15.08% (week-week) and 16.95% (month-week).

Religion on Twitter : communalization in event-based hashtag discourses

Religion on Twitter : communalization in event-based hashtag discourses

Cyberbullying detection on twitter using Big Five and Dark Triad features

This paper presents a cyberbullying detection model based on user personality, determined by the Big Five and Dark Triad models. The model aims to recognize bullying patterns among Twitter communities, based on relationships between personality traits and cyberbullying. Random Forest, a well-known machine-learning algorithm was used for cyberbullying classification (i.e. aggressor, spammer, bully and normal), applied in conjunction with a baseline algorithm encompassing seven Twitter features (i.e. number of mentions, number of followers and following, popularity, favorite count, status count and number of hash tags). Findings indicate that factoring user's personality greatly improves cyberbullying detection mechanisms. Specifically, extraversion, agreeableness and neuroticism (Big Five), and psychopathy (Dark Triad) were found to be significant in detecting bullies, achieving up to 96% (precision) and 95% (recall). The emergence of significant personality traits in an experimental study supports existing empirical studies that show the relationships between personality traits and cyberbullying.

What's in a Hashtag? Feminist Terms for Tweeting in Alliance

What's in a Hashtag? Feminist Terms for Tweeting in Alliance

Pragmatic Reality of Finglish (in Twitter Social Network)

Being a global language English undergoes certain changes and acquires different varieties known as pre-pidgin forms when English serves as a lexificator language. The number of these “Worlds Englishes” is constantly growing and changing, but on the other hand, based on some personal perceptions, we could notice certain reluctance among linguists to examine and describe the language fusions of such kind. The author analyses the concept of World Englishes noting that there is no unity among both Russian and Western linguists towards the terminology and types of World Englishes. Another review covers the mixture of English and Finnish under question that was formed in the US. Special attention is paid to the pshyco-linguistic theories explaining the emergence of both types of pre-pidgins. The author used social network Twitter with “Finglish” as a hash tag as the material for the study. To give a certain estimate to the pragmatic side of it it also carried out a contextual analysis of all the twits with the respective hash tag. The research interest is to specify the connotation, i. e. pragmatic aspect of it that micro context of a twit post might reveal. Overall, we have analyzed 398 twit inscriptions dated from 2009 until 2018. The paper describes three types of pragmatic attitudes to Finglish: neutral (which is typical to the code switching), irony and negative. It is almost impossible to predict whether this pre-pidgin form will develop further or would be restricted (with variable degree of frequency) by social networks and/or informal aural communication, but what is certain is that this form of the language takes place at present and thus linguists cannot ignore it.

PELUANG BISNIS ONLINE SITUS VOUCHER DISKON

<p align="center"><strong>ABSTRACT</strong><strong> </strong><strong></strong></p><p><em>Discount voucher / voucher sites are one part of e-commerce. Rampant discount sites in Indonesia, a separate phenomenon, especially in terms of the development of Internet-based commerce (e-commerce). Discount voucher sites are sites or mobile apps that market advertisements about promos and discounts being held by companies into the world of the internet so that the spread becomes more widespread. With a discount voucher site, companies can advertise their promotions and discounts to the internet. The methodology of data collection is done by observation, namely: direct observation on various voucher and discount voucher sites in Indonesia and with Library Studies, reading books, articles and sites that can assist in the analysis. For marketing strategy done with Organic Marketing, that is by using SEO (Search Engine Optimization) Hash Tags, Meta Tags, Achor Links that must be applied into the website, outside of the side of the website, organic marketing can also be done by way of broadcasting and social media press. For offline marketing channels, discount voucher sites can be made by distributing flyers to public places, such as malls, to inform the public that there is a discount voucher Site presence that they can download using a smartphone. Business analysis is carried out by assessing business feasibility studies in terms of financial aspects. Based on the calculation of investment feasibility study, by using the method of payback period, net present value, internal rate of return, and profability index, it can be concluded that discount voucher sites deserve to be a business opportunity.</em><em></em></p><p><em> </em></p><p><strong><em>Keywords</em></strong><strong><em> : E-commerce, Discount Vouchers, Investment Feasibility Study</em></strong><em></em></p>

Enunciação aforizante no Twitter: uma análise discursiva da hashtag #aprendinoenem

Neste trabalho, analisamos postagens que, indexadas com a hashtag #aprendinoenem e publicadas no Twitter, nos dias de aplicacao do Exame Nacional do Ensino Medio (Enem) de 2015, contem uma logica de citacao dos itens apresentados no exame. Procuramos verificar a hipotese de que essas postagens sejam enunciacoes aforizantes, segundo a definicao de Dominique Maingueneau. Concluimos que as postagens analisadas, ao destextualizarem fragmentos de itens do Enem, veiculam imagens que, construidas na e pela enunciacao, visam contestar a autoridade do exame.Palavras-chave: enunciacao aforizante, Twitter, Enem.

Hashtagging for Health Promotion: Constructing Meaning as an #AntibioticGuardian

This paper aims at investigating how the hashtag constructs meanings in public health campaigns in Twitter. These may have peculiar features due to the simultaneous influence of the character-constrained mode of Twitter, and of the conventional set of communication activities adopted to ensure their effectiveness. The research is based on a corpus of sample tweets (N=2,438) taken from #AntibioticGuardian, a campaign led by Public Health England to reduce Antimicrobial Resistance (AMR). The lexicogrammatical realisations, evaluative language and predominant discourse functions are analysed to seek the meanings that the hashtag can construct in each of the four communication activities, namely increasing awareness and knowledge, providing cues for action, demonstrating simple skills, and changing and/or reinforcing attitudes and behaviours. The method of positive discourse analysis (PDA) used offers the advantage of highlighting how the positive change advocated takes place linguistically; micro and macro data findings reveal a significant user-generated content (UGC) pattern reflecting new ways of making meaning, which moves far beyond the more traditional tagging practices.

#Янебоюсьсказати в повестке украинских и российских СМИ: специфика восприятия инициативы граждан в конфликтной среде масс-медиа

Наталия Александровна Стеблина – кандидат наук по социальным коммуникациям, доцент, кафедра рекламы и связей с общественностью, Одесский национальный университет им. И. И. Мечникова, Одесса, Украина. Электронная почта: steblyna@onu.edu.ua
 Хештег #янебоюсьсказати вследствие популярности в социальных сетях стал предметом интереса для масc-медиа Украины и России. Масштабный флешмоб раскрыл проблемы агрессии против женщин, нарушения их прав и скрытый гендерный конфликт. Анализ восприятия этой акции в СМИ дает возможность проследить специфику формирования медиа-события. На основе анализа делаются выводы об особенностях отражения в СМИ инициатив граждан в эпоху новых медиа. Хотя исследования показывают, что масc-медиа по-прежнему зависимы от традиционных («авторитетных») источников информации, флешмоб #янебоюсьсказати, напротив, стал примером вовлечения в повестку СМИ мнения обычных людей, которые заявили о существовании замалчиваемой проблемы. Для выявления специ­фики подачи подобного материала, проведен анализ основных фреймов, которые использовали наиболее популярные масс-медиа Украины и России. Выделены и исследованы два основных фрейма: фрейм конфликта и фрейм ответственности. Они направлены не столько на решение проблемы насилия в отношении женщин, которая обсуждалась в социальных сетях, сколько на интерпретацию самого флешмоба, его целей и возможных угроз для участников и для общества. В процессе освещения флешмоба #янебоюсьсказати в масс-медиа редко упоминалась необходимость решения проблемы насилия на законодательном уровне. Напротив, СМИ цитировали публикации пользователей соцсетей для привлечения внимания к своим материалам. Наряду с этим публиковались истории знаменитостей, мнения экспертов. Также зафиксированы попытки противопоставить участников дискуссии друг другу. В СМИ делались прогнозы о всплесках насилия, которые могут быть вызваны флешмобом, а сама акция интерпретировалась как повод для подозрений: инициаторов обвиняли в попытках отвлечь общественность от более серьезных тем, например, войны на Востоке Украины. В результате такой подачи информации СМИ скорее заняли пассивную роль, не воспринимая инициативы пользователей социальных сетей всерьез и не предлагая механизмов решения проблем, которые были ими подняты.

The last will be the first a study of European issue publics on Twitter

This article analyzes topics of European relevance on Twitter. It does so by examining #schengen and #ttip Twitter hashtags as a case study. The purpose of this article is to detect which accounts are most important in terms of the number of ties received, and whether they are elite or non-elite actors. This is done by calculating the in-degree and out-degree scores of nodes involved in the networks generated by the usage of the two hashtags. The research reveals that it is easier for civil society and citizens to enjoy an important level of attention similar to that of the media, institutions and politicians on topics of European relevance. The outcomes of this research are important when it comes to understanding how a digital platform such as Twitter contributes to bottom-up conversations about relevant European topics. What we learn here about the structure and configuration of these networks helps us obtaining a more fine-grained understanding of new forms of communication and interaction used by citizens, and their implications for the emergence of a European Public Sphere.

Content, Accessibility, and Dissemination of Disaster Information via Social Media During the 2016 Louisiana Floods.

Social media is becoming increasingly integrated into disaster response communication strategies of public health and emergency response agencies. We sought to assess the content, accessibility, and dissemination of social media communications made by government agencies during a disaster response. A cross-sectional analysis of social media posts made by federal, state, and local government, public health and emergency management agencies before, during, and after the 2016 Louisiana floods was conducted to determine their content, accessibility, and dissemination by level of government and time relative to disaster onset. Facebook and/or Twitter posts made by public agencies involved in the response to the 2016 Louisiana Flooding events (FEMA Disaster Declaration [DR-4277]) published between August 4 and September 16, 2016, publicly available online between February 21 and March 31, 2017, were included in the analysis. Content: The text of each post was assessed to determine whether it contained information on provision of situational awareness; addressing misconception, actionable requests; mental, behavioral, and emotional support; and/or recovery and rebuilding resources. Accessibility: A Flesh-Kincaid grade level of each post was calculated, and information on post language, originality, hyperlinks, visuals, videos, or hash tag was recorded. Dissemination: The average number of reacts/likes, shares/retweets, and comments per post was calculated. Most posts contained information related to situational awareness and recovery resources. There was an increase in messages during the first week of the disaster at all levels. Few posts were made in languages other than English. Compared with state and federal posts, local Facebook posts averaged fewer reacts, comments, and shares throughout the analysis period. Government agencies may maximize the use of social media platforms for disaster communications by establishing their social media network in advance of a disaster and by applying established guidelines on disaster social media use.

Hashtag #Affect

Hashtag #Affect