scholarly journals Using Social Media in Tourist Sentiment Analysis: A Case Study of Andalusia during the Covid-19 Pandemic

2021 ◽  
Vol 13 (7) ◽  
pp. 3836
Author(s):  
David Flores-Ruiz ◽  
Adolfo Elizondo-Salto ◽  
María de la O. Barroso-González
Keyword(s):  
Social Media ◽  
Sentiment Analysis ◽  
Cost Savings ◽  
Mass Scale ◽  
Tourism Sector ◽  
The Social ◽  
Analytical Tools ◽  
Media Data

This paper explores the role of social media in tourist sentiment analysis. To do this, it describes previous studies that have carried out tourist sentiment analysis using social media data, before analyzing changes in tourists’ sentiments and behaviors during the COVID-19 pandemic. In the case study, which focuses on Andalusia, the changes experienced by the tourism sector in the southern Spanish region as a result of the COVID-19 pandemic are assessed using the Andalusian Tourism Situation Survey (ECTA). This information is then compared with data obtained from a sentiment analysis based on the social network Twitter. On the basis of this comparative analysis, the paper concludes that it is possible to identify and classify tourists’ perceptions using sentiment analysis on a mass scale with the help of statistical software (RStudio and Knime). The sentiment analysis using Twitter data correlates with and is supplemented by information from the ECTA survey, with both analyses showing that tourists placed greater value on safety and preferred to travel individually to nearby, less crowded destinations since the pandemic began. Of the two analytical tools, sentiment analysis can be carried out on social media on a continuous basis and offers cost savings.

scholarly journals Bi-Lingual (English, Punjabi) Sarcastic Sentiment Analysis by using Classification Methods

2019 ◽  
Vol 8 (9) ◽  
pp. 1383-1388
Keyword(s):  
Social Media ◽  
Sentiment Analysis ◽  
Main Step ◽  
Online Data ◽  
Social Media Data ◽  
The Social ◽  
Negative Comments ◽  
Regional Languages ◽  
Media Data ◽  
Day By Day

Sentiment analysis is one of the heated topic in the field of text mining. As the social media data is increased day by day the main need of the data scientists is to classify the data so that it can be further used for decision making or knowledge discovery. Now –a-days everything and everyone available online so to check the latest trends in business or in daily life one must consider the online data. The main focus of sentiment analysis is to focus on positive or negative comments so that a well define picture is created that what is trending or not but the sarcasm manipulates the data as in sarcastic comment negative comment consider as positive because of the presence of positive words in the comment or data so it is necessary to detect the sarcasm in online data . The data on social media is available in various languages so sentiment analysis in regional languages is also a main step . In the proposed work we focus on two languages i.e Punjabi and English. Here we use deep learning based neural networks for the sarcasm detection in English as well as Punjabi language. In the proposed work we consider three datasets i.e. balanced English dataset, Balanced Punjabi Dataset and unbalanced Punjabi dataset. We used six different models to check the accuracy of the classified data the models we used are LSTM with word embedding layer, BiLSTM with , LSTM+LSTM, BiLSTM+BiLSTM, LSTM+BiLSTM, CNN respectively. LSTM provide better accuracy for balanced Punjabi and English dataset i.e. 95.63% and 94.17% respectively. The accuracy for unbalanced Punjabi dataset is provided by BiLSTM i.e.96.31%.

scholarly journals Visual Sentiment Analysis on Social Media Data

2021 ◽  
pp. 366-372
Author(s):  
Harshala Bhoir ◽  
K. Jayamalini
Keyword(s):  
Social Media ◽  
Sentiment Analysis ◽  
State Of The Art ◽  
Social Media Data ◽  
Media Image ◽  
The Social ◽  
Textual Data ◽  
Art Works ◽  
Negative Sentiment ◽  
Media Data

Visual sentiment analysis is the way to automatically recognize positive and negative emotions from images, videos, graphics, stickers etc. To estimate the polarity of the sentiment evoked by images in terms of positive or negative sentiment, most of the state-of-the-art works exploit the text associated to a social post provided by the user. However, such textual data is typically noisy due to the subjectivity of the user which usually includes text useful to maximize the diffusion of the social post. Proposed system will extract and employ an Objective Text description of images automatically extracted from the visual content rather than the classic Subjective Text provided by the user. The proposed System will extract three views visual view, subjective text view and objective text view of social media image and will give sentiment polarity positive, negative or neutral based on hypothesis table.

scholarly journals SCRAPING OF SOCIAL MEDIA DATA USING PYTHON-3 AND PERFORMING DATA ANALYTICS USING MICROSOFT POWER BI.

2020 ◽  
Vol 9 (7) ◽  
pp. 66-79
Keyword(s):  
Social Media ◽  
Sentiment Analysis ◽  
Data Analytics ◽  
Marketing Strategies ◽  
Social Media Data ◽  
The Social ◽  
The Right ◽  
Media Data ◽  
Course Of Study

The manifestation of humanity is driven by fulfillment of desires. These desires are satiated by the society and its resources. But after the advent of social media the societal boundaries have shrunken but desires haven’t, hence the desires are now fulfilled through social media. The aforementioned phenomenon was recognized by the business plutocrats very early and have started to satisfy human desires using social media as a tool. But before satisfying the desires, the businesses needs to identify the specific desires of an individual. The identification of specific desires/needs will help the marketing agencies to develop user specific marketing strategies. These desires are explicitly available through the expressions of sentiments in the social media. The sentiment analysis can provide an insight to the desires of an individual. These patterns and insights helps the businesses to market their product to the right person. The sentiments and expressions can be captured using the scraping technique. The aforesaid points highlight’s the course of study followed by this paper and it is to perform data analytics of the social media data scraped using python.

scholarly journals SUMBANGAN BAHASA INDONESIA TERHADAP PEMEKARAN KOSAKATA BAHASA BUGIS: KASUS PENGGUNAAN BAHASA BUGIS PADA MEDIA SOSIAL FACEBOOK (The Contribution of Indonesian Language on Buginese Vocabulary Development: A Case Study of the Use of Buginese on Facebook Social Media)

SAWERIGADING ◽  
2019 ◽  
Vol 25 (2) ◽  
pp. 107
Author(s):  
Muhammad Darwis ◽  
Kamsinah Kamsinah
Keyword(s):  
Social Media ◽  
Research Strategies ◽  
Loan Words ◽  
Code Mixing ◽  
Word Categorization ◽  
The Social ◽  
Data Source ◽  
Media Data ◽  
Bahasa Indonesia

AbstrakThe aim of this research is: (1) to identify the forms and categories of Indonesian words that are absorbed into Buginese sentences and (2) to reveal the reasons for the use of Indonesian elements into Buginese sentences by Facebookers in the social media. Data on this qualitative research obtained from social media ‘Facebook’. The data source of this research is the Facebookers who are members of the MABBASA UUGIE KU PESBU’ group, November 2013 to April 2014 edition. Data analyzed are Buginese sentences consisting of three to five examples of Buginese sentences containing Indonesian elements in the form of words, phrases or clauses taken purposively. Furthermore, the analysis was carried out with grounded research strategies. The results of this research indicate that (1) Buginese language can survive as a means of communication within Buginese ethnic groups when writing on the social media ‘Facebook’, due to they have obtained vocabulary contributions from Indonesian in the form of the basic word, affixation word, and phrase. In word categorization, the loan words consist of nouns, verbs, adjectives, and conjunctions. Then, (2) the use of the Indonesian language elements has four main reasons, namely (a) filling in the blanks, (b) adding equivalence variations, (c) clarifying the meaning, and (d) interference. Reasons (a) to (c) can take the form of code-mixing and code-switching. AbstrakPenelitian ini bertujuan: (1) mengidentifikasi bentuk dan kategori kata bahasa Indonesia (bI) yang  terserap ke dalam kalimat-kalimat bahasa Bugis (bB) dan (2) mengungkap alasan-alasan penggunaan unsur-unsur bI tersebut ke dalam kalimat bB oleh para Facebooker di media sosial. Data penelitian kualitatif ini diperoleh dari media sosial Facebook. Sumber data penelitian ini ialah para Facebooker yang menjadi anggota grup MABBASA UUGIE KU PESBU’ edisi bulan November 2013 s.d. bulan April 2014. Data yang dianalisis ialah kalimat-kalimat ber-bB yang terdiri atas tiga sampai lima contoh kalimat ber-bB yang berisi unsur-unsur bI, yang berupa kata, frasa, atau klausa, yang diambil secara purposif. Selanjutnya, analisis dilakukan dengan upaya grounded research. Hasil penelitian ini menunjukkan bahwa (1) bB dapat bertahan hidup sebagai sarana perhubungan intern suku Bugis dalam komunikasi tulisan sosial Facebook karena memperoleh sumbangan kosakata bI yang berbentuk kata dasar, kata berimbuhan, dan frasa atau ungkapan. Dari segi kategorisasi kata, unsur-unsur serapan tersebut terdiri atas kata benda, kata kerja, kata sifat, dan kata sambung. Kemudian, (2) penggunaan unsur-unsur bI tersebut memiliki empat alasan utama, yaitu (a) mengisi kekosongan, (b) menambah variasi kesepadanan, (c) memperjelas pemaknaan, dan (d) interferensi. Alasan (a) sampai dengan (c) dapat mengambil bentuk campur kode dan alih kode.   

Entrepreneurship and Innovation in Tourism E-Businesses

2020 ◽  
pp. 159-176
Author(s):  
Pedro Álvaro Pereira Correia ◽  
Irene García Medina ◽  
Zahaira Fabiola González Romo
Keyword(s):  
Social Networks ◽  
Social Media ◽  
Social Factors ◽  
Exploratory Analysis ◽  
Competitive Advantages ◽  
Strategic Vision ◽  
Tourism Sector ◽  
The Social ◽  
Share Information

The emergence of social networks has revolutionized the way people communicate and share information. Consequently, it becomes important to analyze the role of these models of collaboration and innovation through social networks in the strategic vision of the responsibility of marketing and communication in tourism industries, mainly the role of Facebook in e-business actions. This chapter presents a qualitative and exploratory analysis of the individuals in the virtual context of the social media, their behaviors, reactions, and attitudes, to perceive which social factors can enhance the appearance of competitive advantages for the organizations. There was a predilection for companies with a greater international connection at the level of clients and also at the level of the operation because there was a predominance of companies related to the tourism sector of Madeira.

Visual Social Media and Big Data. Interpreting Instagram Images Posted on Twitter

2016 ◽  
Vol 2 (2) ◽  
pp. 113-134 ◽  
Author(s):  
Dhiraj Murthy ◽  
Alexander Gross ◽  
Marisa McGarry
Keyword(s):  
Social Media ◽  
Image Data ◽  
Hurricane Sandy ◽  
Social Media Data ◽  
Production And Consumption ◽  
The Social ◽  
Application Programming ◽  
Programming Interfaces ◽  
Media Data

Abstract Social media such as Twitter and Instagram are fast, free, and multicast. These attributes make them particularly useful for crisis communication. However, the speed and volume also make them challenging to study. Historically, journalists controlled what/how images represented crises. Large volumes of social media can change the politics of representing disasters. However, methodologically, it is challenging to study visual social media data. Specifically, the process is usually labour-intensive, using human coding of images to discern themes and subjects. For this reason, Studies investigating social media during crises tend to examine text. In addition, application programming interfaces (APIs) for visual social media services such as Instagram and Snapchat are restrictive or even non-existent. Our work uses images posted by Instagram users on Twitter during Hurricane Sandy as a case study. This particular case is unique as it is perhaps the first US disaster where Instagram played a key role in how victims experienced Sandy. It is also the last major US disaster to take place before Instagram images were removed from Twitter feeds. Our sample consists of 11,964 Instagram images embedded into tweets during a twoweek timeline surrounding Hurricane Sandy. We found that the production and consumption of selfies, food/drink, pets, and humorous macro images highlight possible changes in the politics of representing disasters - a potential turn from top-down understandings of disasters to bottom-up, citizen informed views. Ultimately, we argue that image data produced during crises has potential value in helping us understand the social experience of disasters, but studying these types of data presents theoretical and methodological challenges.

The Role of the Partner Brand's Social Media Power in Brand Alliances

2018 ◽  
Vol 82 (3) ◽  
pp. 25-44 ◽  
Author(s):  
Ann-Kristin Kupfer ◽  
Nora Pähler vor der Holte ◽  
Raoul V. Kübler ◽  
Thorsten Hennig-Thurau
Keyword(s):  
Social Media ◽  
Data Set ◽  
Brand Alliance ◽  
The Social ◽  
Composite Product ◽  
Product Sales ◽  
Media Power ◽  
Media Data ◽  
Social Media Network

Managers frequently seek strategies to profit systematically from social media to increase product sales. By forming a brand alliance, they can acquire an installed social media base from a partner brand in an attempt to boost the sales of their composite products. Drawing from power theory, this article develops a conceptual model of the influence of the social media power of partner brands on brand alliance success. The proposed framework details the partner brand's social media power potential (size and activity of the social media network), social media power exertion (different posting behaviors and comments), and their interaction. The authors test this framework with an extensive data set from the film industry, in which films function as composite products and actors represent partner brands. The data set features 442 movies, including 1,318 actor–movie combinations and weekly social media data (including 41,547 coded Facebook posts). The authors apply a linear mixed-effects model, in which they account for endogeneity concerns. The partner brand's social media power potential, power exertion, and their interaction can all lead to higher composite product sales. By coding different types of product-related posts, this article provides estimates of their varying monetary value.

Competitive intelligence in social media Twitter: iPhone 6 vs. Galaxy S5

2016 ◽  
Vol 40 (1) ◽  
pp. 42-61 ◽  
Author(s):  
Yoosin Kim ◽  
Rahul Dwivedi ◽  
Jie Zhang ◽  
Seung Ryul Jeong
Keyword(s):  
Social Media ◽  
Sentiment Analysis ◽  
Purchase Intention ◽  
Opinion Mining ◽  
Sales Performance ◽  
Competitive Intelligence ◽  
Social Media Data ◽  
Content Type ◽  
The Social ◽  
Media Data

Purpose – The purpose of this paper is to mine competitive intelligence in social media to find the market insight by comparing consumer opinions and sales performance of a business and one of its competitors by analyzing the public social media data. Design/methodology/approach – An exploratory test using a multiple case study approach was used to compare two competing smartphone manufacturers. Opinion mining and sentiment analysis are conducted first, followed by further validation of results using statistical analysis. A total of 229,948 tweets mentioning the iPhone6 or the GalaxyS5 have been collected for four months following the release of the iPhone6; these have been analyzed using natural language processing, lexicon-based sentiment analysis, and purchase intention classification. Findings – The analysis showed that social media data contain competitive intelligence. The volume of tweets revealed a significant gap between the market leader and one follower; the purchase intention data also reflected this gap, but to a less pronounced extent. In addition, the authors assessed whether social opinion could explain the sales performance gap between the competitors, and found that the social opinion gap was similar to the shipment gap. Research limitations/implications – This study compared the social media opinion and the shipment gap between two rival smart phones. A business can take the consumers’ opinions toward not only its own product but also toward the product of competitors through social media analytics. Furthermore, the business can predict market sales performance and estimate the gap with competing products. As a result, decision makers can adjust the market strategy rapidly and compensate the weakness contrasting with the rivals as well. Originality/value – This paper’s main contribution is to demonstrat the competitive intelligence via the consumer opinion mining of social media data. Researchers, business analysts, and practitioners can adopt this method of social media analysis to achieve their objectives and to implement practical procedures for data collection, spam elimination, machine learning classification, sentiment analysis, feature categorization, and result visualization.

scholarly journals Social media as the platform for political mobilization: case study of Kazakhstan

2020 ◽  
Vol 338 ◽  
pp. 431-442
Author(s):  
Assem Kalkamanova
Keyword(s):  
Social Media ◽  
Political Mobilization ◽  
Political Elite ◽  
Protest Movements ◽  
Announcement Date ◽  
The Social ◽  
Social Media Platforms ◽  
The Government

This paper focuses on the role of social media in the rise of the protest movements and political mobilization in Kazakhstan. The country has been seeing an increase in the social networks based civil activists since recently. I argue that the emergence of the Democratic Choice of Kazakhstan that operates only within the realm of social media platforms promoted political activism and civil protests in the country. Most importantly, I argue that in contrast to the conclusions of the Kazakhstani court’s decision in March 2018, the movement leader’s Facebook blog reveals no violence either towards the government or some specific political elite. Using text mining methods, I analyzed the texts of his Facebook posts from the announcement date in 2017 till the end of 2019: the rhetoric of the position of the Democratic Choice is informational, first, and protest calling, second. Also, the analysis of seven most popular political Youtube bloggers shows that the people’s discontent with injustices and undemocratic polity manifested in the poignant interest towards the creator of this system, Mr. Nazarbayev and his closest circle. The SMM software allowed to find out the areas of Kazakhstani politics that are of most interest to the audience of Kazakhstani political activists.

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