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Journal articles on the topic 'Twitter behaviour'

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Author: Grafiati
Published: 10 December 2022
Last updated: 29 January 2023

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1

ALGARNI, ABDULLAH AHMED. "THE ROLE OF SOCIAL NETWORKS IN PROMOTING POSITIVE BEHAVIOUR DURING COVID-19 CRISIS AMONGST A SAMPLE OF USERS IN SAUDI SOCIETY: TWITTER AS A MODEL." AD ALTA: 12/01 12, no. 1 (June 30, 2022): 7–16. http://dx.doi.org/10.33543/1201716.

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This study seeks analysing Twitter social network role in promoting positive behaviour during COVID-19 crisis and exploring the relationship between them. It targets identifying Twitter positive behaviour level differences through variables of gender, age, marital status, residence status, administrative region, and Twitter using size. An online questionnaire was used on a validity-and-stability verified sample of (586) individual Twitter users in the Kingdom of Saudi Arabia. Sample members approved Twitter users’ positive behaviour during COVID-19 crisis. They agreed that the positive behaviour level was medium with a Twitter effect of (19.4%). There were both a positive, medium-strong correlation between Twitter daily use and a statistically significant correlation between one - session Twitter using and positive behaviour promotion. However, there were statistically significant differences in positive behaviour promotion when using Twitter between social status favouring singles, residence status favouring residents, age favouring those under 21, administrative region favouring the southern region, usage period favouring network daily and two days - users, and browsing time favouring much Twitter users .The study recommends conducting studies on positive social behaviour and its dimensions to broadly generalise results. Studies on the Internet of behaviour and artificial intelligence are needed to analyse the positive behaviour expected by social networks users to enhance opportunities. It also stressed children and adolescents’ digital social education to prepare community members for effective online participation, the activation of public and private services-providing agencies Twitter accounts, interacting positively with users' questions and responses, and substituting fixed stereotypes by interesting interactive patterns.
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Klotz, Christine, Coskun Akinalp, and Herwig Unger. "Clustering user behaviour patterns on Twitter." International Journal of Social Network Mining 2, no. 3 (2016): 203. http://dx.doi.org/10.1504/ijsnm.2016.082632.

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Akinalp, Coskun, Christine Klotz, and Herwig Unger. "Clustering user behaviour patterns on Twitter." International Journal of Social Network Mining 2, no. 3 (2016): 203. http://dx.doi.org/10.1504/ijsnm.2016.10003518.

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Gabriel, T. Nyitse, Terhile Agaku, and Cordelia Clayton. "Influence of Social Media on Abuja Youths Behaviour in 2019 General Elections: A Study of Twitter." RESEARCH JOURNAL OF MASS COMMUNICATION AND INFORMATION TECHNOLOGY 8, no. 1 (October 6, 2022): 63–74. http://dx.doi.org/10.56201/rjmcit.v8.no1.2022.pg63.74.

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This study ‘‘Influence of Social Media on Abuja Youths Voting Behaviour in 2019 General Elections: a study of Twitter’’ was conducted to ascertain how Twitter can be engaged as a platform for influencing voting behaviour particularly on youths in the city of Abuja. Anchored on Technology Determinism theory. the survey research design was adopted with online questionnaire as instrument for data collection, on a sample size of 100 respondents. Findings from the study revealed that ‘Twitter’ as a social media platform play a vital role in influencing youths, the study also found out that ‘Twitter’, was effective in enhancing voters behavior. Based on the findings the study concludes that Twitter which is one of the most common social media platform especially among youths, play crucial role in influencing voters behavior to some extent, despite the challenge of it being banned by the Federal Government lately. Thus the study recommends that more political parties should be encouraged to have a noticeable presence on the internet. Also the Federal Government should intensify its ICT drive in education and other sectors of the country as the reach of the social media surpasses that of any traditional media
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Azwar, Azmiera Izzati, and Suet Nie Kho. "Factors Influencing Young Malaysians’ Political Information Seeking Behaviour on Twitter." Jurnal Komunikasi: Malaysian Journal of Communication 38, no. 3 (September 30, 2022): 87–105. http://dx.doi.org/10.17576/jkmjc-2022-3803-06.

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Youth participation in political discourses is an important element that needs to be looked into urgently in Malaysia. This is especially so with the historical milestone of the Undi18 constitutional amendment allowing youth from 18 years old to vote in the 15th General Election. This research was initiated to investigate the youth's behaviour in terms of attitude, awareness, and involvement in politics via social media, specifically Twitter. In this study, involvement in politics is described as youths' political information seeking behaviour on Twitter in relation to political attitudes such as political self-efficacy, situational political involvement, government trust, and processing of information, that is perceived information quality. An online survey form was disseminated across Twitter using snowball sampling for Klang Valley Twitter users aged between 18 to 30. The results garnered from 314 respondents revealed significant relationships between independent variables (self-efficacy, situational, political involvement, government trust, and information quality) and the dependent variable (Twitter motivation). It was hoped that this study would help researchers better grasp the pattern on how Malaysian youth use Twitter to get political information. This study may also provide important information on the online diffusion and consumption of political information through social media like Twitter. Keywords: Political information-seeking behaviour, processing information, youth, Twitter, Malaysia.
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Rachmawati, Iva, Machya Astuti Dewi, Frans Richard Kodong, and Panji Dwi Ashrianto. "Trump and Biden's Covid 19 Policy Narrative on Twitter." RSF Conference Series: Business, Management and Social Sciences 1, no. 4 (October 22, 2021): 1–17. http://dx.doi.org/10.31098/bmss.v1i4.280.

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Social media can be one of the tools of state diplomacy to provide information to the public, change public perceptions and ultimately influence public behaviour. During the pandemic, social media has become one of the strategic diplomatic tools to reach the public and governments of other countries. In addition to conveying information about state policies in dealing with the pandemic, social media is also a means for the state to influence the public and other countries in taking a stand against the pandemic. This article looks at the policies and communication efforts of the two American Presidents on Twitter social media related to the Covid19 Pandemic through the descriptive analysis method. A structural approach to the concept of social media diplomacy is used to show that the narrative on Twitter influences the perception and behaviour of its users. This research found that the different narratives on Twitter and the differences in user perceptions and behaviours, indicating that social media diplomacy has a real impact on user perceptions and behaviour.
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Hodeghatta, Umesh Rao, and Sangeeta Sahney. "Understanding Twitter as an e-WOM." Journal of Systems and Information Technology 18, no. 1 (March 14, 2016): 89–115. http://dx.doi.org/10.1108/jsit-12-2014-0074.

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Purpose – This paper aims to research as to how Twitter is influential as an electronic word-of-mouth (e-WOM) communication tool and thereby affecting movie market. In present days, social media is playing an important role in connecting people around the globe. The technology has provided a platform in the social media space for people to share their experiences through text, photos and videos. Twitter is one such online social networking media that enables its users to send and read text-based messages of up to 140 characters, known as “tweets”. Twitter has nearly 200 million users and billions of such tweets are generated by users every other day. Social media micro-blogging broadcasting networks such as Twitter are transforming the way e-WOM is disseminated and consumed in the digital world. Twitter social behaviour for the Hollywood movies has been assessed across seven countries to validate the two basic blocks of the honeycomb model – sharing and conversation. Twitter behaviour was studied for 27 movies in 22 different cities of seven countries and for six genres with a total tweets of 9.28 million. The difference of Twitter social media behaviour was compared across countries, and “sharing” and “conversation” as two building blocks of the honeycomb model were studied. t-Test results revealed that the behaviour is different across countries and across genres. Design/methodology/approach – The objective of the paper is to analyse Twitter messages on an entertainment product (movies) across different regions of the world. Hollywood movies are released across different parts of the world, and Twitter users are also in different parts of the world. The objective is to hence validate “conversation” and “sharing” building blocks of the honeycomb model. The research is confined to analysing Twitter data related to a few Hollywood movies. The tweets were collected across nine different cities spanning four different countries where English language is prominent. To understand the Twitter social media behaviour, a crawler application using Python and Java was developed to collect tweets of Hollywood movies from the Twitter database. The application has incorporated Twitter application programming interfaces (APIs) to access the Twitter database to extract tweets according to movies search queries across different parts of the world. The searching, collecting and analysing of the tweets is a rather challenging task because of various reasons. The tweets are stored in a Twitter corpus and can be accessed by the public using APIs. To understand whether tweets vary from one country to another, the analysis of variance test was conducted. To assess whether Twitter behaviour is different, and to compare the behaviour across countries, t-tests were conducted taking two countries at a time. The comparisons were made across all the six genres. In this way, an attempt was made to obtain a microscopic view of the Twitter behaviour for each of the seven countries and the six genres. Findings – The findings show that the people use social media across the world. Nearly 9.28 million tweets were from seven countries, namely, USA, UK, Canada, South Africa, Australia, India and New Zealand for 27 Hollywood movies. This is indicative of the fact that today, people are exchanging information across different countries, that people are conversing about a product on social media and people are sharing information about a product on social media and, thus, proving the hypothesis. Further, the results indicate that the users in USA, Canada and UK, tweet more than the other countries, USA and UK being the highest in tweets followed by the Canada. On the other hand, the number of tweets in Australia, India and South Africa are low with New Zealand being the lowest of all the countries. This indicates that different countries’ users have different social media behaviour. Some countries use social media to communicate about their experience more than in some other country. However, consumers from all over the world are using Twitter to express their views openly and freely. Originality/value – This research is useful to scholars and enterprises to understand opinions on Twitter social media and predict their impact. The study can be extended to any products which can lead to better customer relationship management. Companies can use the Internet and social media to promote and get feedback on their products and services across different parts of the world. Governments can inform the public about their new policies, benefits of governmental programmes to people and ways to improve the Internet reach to more people and also for creating awareness about health, hygiene, natural calamities and safety.
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DÜNDAR, Mahire Armağan, and Fırat TUFAN. "Sosyal Ağ Sitelerinde Sosyal Karşılaştırma Davranışı: Instagram- Twitter Karşılaştırması." Yeni Medya Dergisi 2022, no. 12 (June 30, 2022): 1–16. http://dx.doi.org/10.55609/yenimedya.1051044.

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The purpose of this study is to examine social comparison behavior on social networking sites (SNS). Quantitative research method based on the closed-ended questionnaire technique was used in the study in which social comparison behavior was examined on image-based SNS, Instagram and text-based SNS, Twitter. Findings show that; individuals make social comparisons more in physical environments than on SNS. The level of social comparison is higher on Instagram compared to Twitter. Individuals are more frequently engaged in upward comparisons than downward comparisons on both Instagram and Twitter. Wealth is the domain in which individuals make comparisons the most on Instagram while the prominent comparison domain on Twitter is success. Inspiration is an emotion experienced most by individuals towards upward comparisons, whereas sympathy is the most experienced emotion by individuals towards downward comparisons on both Instagram and Twitter. There is no relation between social comparison level and frequency of SNS use.
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9

Roenneberg, Till. "Twitter as a means to study temporal behaviour." Current Biology 27, no. 17 (September 2017): R830—R832. http://dx.doi.org/10.1016/j.cub.2017.08.005.

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Johnson, Michiel, Steve Paulussen, and Peter Van Aelst. "The manifest and latent functions of Twitter use by journalists: An observational study among economic journalists." Journal of Applied Journalism & Media Studies 8, no. 3 (November 1, 2019): 311–29. http://dx.doi.org/10.1386/ajms_00004_1.

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This study focuses on Twitter use among economic journalists working for print media in Belgium. By looking into their tweeting and following behaviour, the article examines how economic journalists use Twitter for promotional, conversational and sourcing purposes. Based on an automated content analysis of what they tweet and a social network analysis of whom they follow, the results show that economic journalists mainly use Twitter to promote themselves and their news organization rather than to engage in public conversation on the platform. In addition, the study looks into their following behaviour to investigate which actors they consider as 'potential sources'. Here, the findings are consistent with previous studies among political and health journalists, indicating that journalists are more likely to follow institutionally affiliated rather than non-affiliated sources on Twitter. Furthermore, the social network analysis gives additional evidence of the media-centered of journalists' Twitter use, as media-affiliated actors maintain a dominant position in the economic journalists' Twitter networks.
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Meier, Florian, David Elsweiler, and Max Wilson. "More than Liking and Bookmarking? Towards Understanding Twitter Favouriting Behaviour." Proceedings of the International AAAI Conference on Web and Social Media 8, no. 1 (May 16, 2014): 346–55. http://dx.doi.org/10.1609/icwsm.v8i1.14541.

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Microblogging services, such as Twitter, offer a variety of interactive features that allow users to engage with contacts in their social network and the content they produce. One such feature is the favourite button on Twitter, an icon in the form of a star that users can click on to assign a special status to a particular tweet. Despite evidence suggesting that users increasingly make use of favouriting, little is known about the reasons people have for favouriting or the utility the feature offers. This contrasts with other core features, such as “following” and “retweeting”, which have been studied extensively. In this paper we argue that by investigating the motivations for favouriting tweets we can enhance our understanding of what people want to achieve with Twitter and the types of content users find interesting or useful. With these goals in mind we conducted a large-scale survey (n=606), questioning Twitter users on various aspects of their favouriting behaviour. Of these users only 395 were aware of the function and 290 make use of the functionality. The survey responses from these users demonstrate that motives for favouriting tweets are extremely heterogeneous and not always consistent within and between users. Moreover, our findings reveal that user needs when favouriting such as the need for re-finding a tweet or the wish for a more private conversation are often poorly supported and sometimes even go unmet by the Twitter user interface.
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Abdul Kadir, Zaemah, Norsyafigah Mohd Ali, Sharifah Shahnaz Syed Husain, and Zurina Zubir. "Gender Differences in Twitter Complaints." Environment-Behaviour Proceedings Journal 7, SI7 (August 31, 2022): 67–74. http://dx.doi.org/10.21834/ebpj.v7isi7.3763.

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This study aimed to identify and compare the different strategies used by males and females in making complaints. Both genders adopt different strategies when making complaints. In this qualitative study, the content analysis method was adopted, and based on Trosborg's Theory of Complaint, complaints messages posted by 23 Twitter users were analyzed. The results showed that males perform dissatisfaction more frequently than females. However, females use blame strategy at a higher frequency than males. This research revealed a new perspective on gender differences and valuable insights influencing complaint-making strategies. Keywords: Complaints, Code-switching, Language Choice, Strategies eISSN: 2398-4287 © 2022. The Authors. Published for AMER ABRA cE-Bs by e-International Publishing House, Ltd., UK. This is an open access article under the CC BYNC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer–review under responsibility of AMER (Association of Malaysian Environment-Behaviour Researchers), ABRA (Association of Behavioural Researchers on Asians) and cE-Bs (Centre for Environment-Behaviour Studies), Faculty of Architecture, Planning & Surveying, Universiti Teknologi MARA, Malaysia. DOI: https://doi.org/10.21834/ebpj.v7iSI7%20(Special%20Issue).3763
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Yoo, Jaeheung, Saesol Choi, Munkee Choi, and Jaejeung Rho. "Why people use Twitter: social conformity and social value perspectives." Online Information Review 38, no. 2 (February 25, 2014): 265–83. http://dx.doi.org/10.1108/oir-11-2012-0210.

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Purpose – Based on social conformity and social value perspectives, the authors aim to empirically examine the critical role of social influences on Twitter user behaviour. Design/methodology/approach – An integrative structural model is developed to explain how social influences, which are divided into social conformity and social values, work with other salient factors such as the utilitarian and hedonic values to affect the use of Twitter. The partial least square method was used to verify the proposed model with usable data from 204 adult Korean Twitter users. Findings – Social conformity positively affects the frequent use of Twitter and it is mediated through perceived values such as the hedonic, utilitarian and social appearance values associated with Twitter use. While social appearance negatively affected the trustworthiness of information shared on Twitter, the social capital effect on Twitter use was insignificant. Research limitations/implications – This study has some limitations for general applicability of the results: the samples include only adult users in Korea, and it is a cross-sectional study for a specific social networking service. This study theoretically disentangles the complicated nature of social influences by proposing two distinct constructs (social conformity and social values) and empirically verifying their significant roles in Twitter use. Practical implications – Practitioners should recognise that the hedonic value of Twitter is the key factor that affects both the quantity and quality of information shared on Twitter. In addition user motivations for pursuing social appearance in SNSs might cause a user to distort the information that they produce. Originality/value – This study provides unique implications related to the role of social conformity, social values and user behaviour on Twitter.
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Marcos-García, Silvia, Laura Alonso-Muñoz, and Amparo López-Meri. "Extending influence on social media: The behaviour of political talk-show opinion leaders on Twitter." Communication & Society 33, no. 2 (April 20, 2020): 277–93. http://dx.doi.org/10.15581/003.33.2.277-293.

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Social media, especially Twitter, has become a strategic space for those users who try to extend their influence in the digital environment. This work focuses on opinion leaders who participate in political talk-shows. The aim is to analyse the use and the thematic agenda proposed by these actors on Twitter during electoral periods. The Twitter profiles of 20 opinion leaders (journalists, media editors and experts) of four Spanish television channels are examined. A quantitative content analysis is used on 2,588 tweets disseminated during the November 2019 general election campaign in Spain by them. Results show differences between the different types of actors who make up the sample. Journalists use Twitter to express their criticisms and reinforce their community of followers, especially using interaction and humour. Media editors are more neutral and promote their personal brand through the promotion of their media companies. Experts inform and analyse political news more than journalists, although they also criticise and respond to citizens’ comments. Regarding the subject agenda, messages on electoral results and media content predominate. Thus, the data shows how opinion leaders take advantage of Twitter to freely show their opinions, especially negative ones, and boost dialogue with users.
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Jadhav, Akash, Apeksha Jadhav, and Reshma Bhosale. "Examine the Behaviour of People to Sociality Using Twitter." IJARCCE 8, no. 1 (January 30, 2019): 36–38. http://dx.doi.org/10.17148/ijarcce.2019.8108.

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Chouhan, Kuldeep, Mukesh Yadav, Ranjeet Kumar Rout, Kshira Sagar Sahoo, NZ Jhanjhi, Mehedi Masud, and Sultan Aljahdali. "Sentiment Analysis with Tweets Behaviour in Twitter Streaming API." Computer Systems Science and Engineering 45, no. 2 (2023): 1113–28. http://dx.doi.org/10.32604/csse.2023.030842.

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Puspita, Rr Sukma Dian, and Gumgum Gumelar. "PENGARUH EMPATI TERHADAP PERILAKU PROSOSIAL DALAM BERBAGI ULANG INFORMASI ATAU RETWEET KEGIATAN SOSIAL DI JEJARING SOSIAL TWITTER." JPPP - Jurnal Penelitian dan Pengukuran Psikologi 3, no. 1 (April 30, 2014): 1. http://dx.doi.org/10.21009/jppp.031.01.

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Abstract This study was conducted to determine the effect of empathy to pro-social behaviour in repeated share information or retweet social activities at social network twitter. The methods was used in this research is quantitative approach. Sampling techniques are using nonprobability sampling technique with kind incidental sampling techniques. The sample was used in this study amounted to 138. Data analysis techniques are use to test the hypothesis is a simple regression test which using SPSS version 16.00. Based on the counting result value F is 185.409 with value of significance is 0.000. The regression similarity of Y= 24.094 + 0.591X and great influence (R Square) a variable empathy to prososial behavior is 0.577, which means that empathy affect the behavior of prososial as much as 57.7% and the rest 42.3% is affected by another factors. Therefore, Ho denied and Ha accepted so it can be concluded that there is a significant positive influence of empathy to the behavior of prososial in sharing information or social activity in a retweet social networking twitter. Keywords: Empathy, Prososial Behavior, Social Networking Twitter
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Afdjani, Hadiono, and Daniel Simanjuntak. "The Strategy of Drama Series "Lonceng Cinta" in Increasing Public Interest Through Social Media Twitter." Environment-Behaviour Proceedings Journal 5, SI1 (June 1, 2020): 47–51. http://dx.doi.org/10.21834/ebpj.v5isi1.2296.

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This study aims to find out how the promotion strategy of television drama series "India Lonceng Cinta" through Twitter conducted by social media team ANTV. The focus of the problem is on the use of social media twitter @seriesANTV and @whatsonANTV in promoting the Indian drama series "Lonceng Cinta" to the public. The development of twitter today, not only as a social media, but ANTV use it as a media promotion of impressions to the people of Indonesia. Theories used are New Media theory and Marketing Communication theory. The paradigm of the research is the postpositivism paradigm, the qualitative approach and the method used is the interistic approach, that is expressing how the social media team strategy in promoting drama series "Lonceng Cinta" using twitter. Keywords: Promotion, Social Media, Twitter, Television Program, Marketing Communications. eISSN: 2398-4287 © 2020. The Authors. Published for AMER ABRA cE-Bs by e-International Publishing House, Ltd., UK. This is an open-access article under the CC BYNC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer–review under responsibility of AMER (Association of Malaysian Environment-Behaviour Researchers), ABRA (Association of Behavioural Researchers on Asians) and cE-Bs (Centre for Environment-Behaviour Studies), Faculty of Architecture, Planning & Surveying, Universiti Teknologi MARA, Malaysia.DOI: https://doi.org/10.21834/ebpj.v5iSI1.2296
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Miller, Robert, and James Melton. "College students and risk-taking behaviour on Twitter versus Facebook." Behaviour & Information Technology 34, no. 7 (January 26, 2015): 678–84. http://dx.doi.org/10.1080/0144929x.2014.1003325.

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Fu, Xin, and Yun Shen. "Study of collective user behaviour in Twitter: a fuzzy approach." Neural Computing and Applications 25, no. 7-8 (June 28, 2014): 1603–14. http://dx.doi.org/10.1007/s00521-014-1642-9.

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Olinski, Marian, and Piotr Szamrowski. "Twitter as an engagement tool: How Public Benefit Organizations are building relationships with their audience." Journal of East European Management Studies 25, no. 2 (2020): 216–45. http://dx.doi.org/10.5771/0949-6181-2020-2-216.

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The current study applies content analysis to scrutinize the relationship between Twitter messaging tactics employed by 186 Public Benefit Organizations (PBO) and public reactions in the form of liking, retweeting and commenting behaviour. The results indicate that Twitter plays a marginal role in the Polish PBO, and it seems to be at most complementary to the much more frequently utilized Facebook. Furthermore, the size of the organization does not affect the frequency of the published content on Twitter. Multiple regression analysis indicated that the most important factor influencing audience engagement was the Twitter profile number of followers. It explained the largest percentage of variance in terms of the average number of retweets, the average number of likes, and the percentage of tweets that were then commented on.
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Alhumoud, Sarah. "Twitter Analysis for Intelligent Transportation." Computer Journal 62, no. 11 (December 20, 2018): 1547–56. http://dx.doi.org/10.1093/comjnl/bxy129.

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Abstract The amount of data available online has grown enormously over the last decade as a result of the rapid growth of smartphone users and the availability of communication applications. Due to the anonymity and instantaneous nature of social media broadcasting compared to conventional attitudinal survey methods, social media mining is becoming popular for complementing traditional traffic detection methods due to its accessibility in reaching a large population and the opportunities for reflecting the true and immediate behaviour of participants for free. This study presents a framework for Arabic Twitter content analysis to gain transportation insight. The study is done with a dataset of more than 1 million tweets collected within 3 months. The proposed model comprises three main components: data acquisition, data analysis and the reverse geotagging scheme (RGS). The RGS tackles the problem of lack of location information in the tweets. Results show that 13% of the dataset reports traffic-related incidents with an overall precision of 55% and 87% for incidents identification prediction without and with reverse geotagging, respectively. This proves the efficiency of the developed analyser in identifying tweets on transportation and the potential of the RGS in defining the location of tweets with no registered location information.
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Sari, Indah Purnama, Aniek Irawatie, and Retno Dyah Kusumastuti. "PENGARUH KOMUNIKASI NCTZEN INDONESIA TERHADAP PERILAKU MEMILIH NCT DREAM." JOURNAL OF DIGITAL EDUCATION, COMMUNICATION, AND ARTS (DECA) 3, no. 01 (April 6, 2020): 40–50. http://dx.doi.org/10.30871/deca.v3i01.1932.

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Social media is a social change tool using the internet where social media used by everyone as their communication process that reaches all levels of society to form a group to talk about something that is in common with the group. NCTzen Indonesia is a fan group from the Kpop idol group, NCT Dream that formed from the social media Twitter, nctconfess. The nctconfess followers are considered to be able to influence the activities and behavior of other followers. This research aims to determine the effect of NCTzen Indonesia's communication through Twitter on the voting behaviour of fellow followers using the S-O-R theory as its foundation. This research uses the quantitative approach with a survey method in the form of questionnaires spread through menfess to 100 respondents in the category of followers of Nctconfess who vote in NCT Dream during the promotion period. The results based on the correlation test show that there is a strong relationship between NCTzen Indonesia's communication and voting behaviour. Referring to the test results of the coefficient of determination, they show that the magnitude of the effect generated by the Communication of NCTzen Indonesia (X) on the Voting Behavior (Y) is 39.81% and the remaining 60.19% is influenced by other factors outside this research.
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Bouvier, Gwen, and David Machin. "What gets lost in Twitter ‘cancel culture’ hashtags? Calling out racists reveals some limitations of social justice campaigns." Discourse & Society 32, no. 3 (April 15, 2021): 307–27. http://dx.doi.org/10.1177/0957926520977215.

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Twitter campaigns attacking those who make racist or xenophobic statements are valuable, raising the public profile of opinions that will not tolerate racism in any form. They also indicate how our major institutions are failing to address important matters of social justice. But there is concern that social media, such as Twitter, tends to extremes, moral outrages, lack of nuance and incivility, which shape how issues become represented. In this paper, using Critical Discourse Analysis, we look at three Twitter hashtags calling-out racist behaviour. We ask how racism and anti-racism is represented on these hashtags? We show how these misrepresent fundamental aspects of racism in society, distracting from, what race theorists would argue, is the most important thing these incidents tell us about racism at this present time. The findings have consequences for all such Twitter social justice campaigns.
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Veltri, Giuseppe A., and Dimitrinka Atanasova. "Climate change on Twitter: Content, media ecology and information sharing behaviour." Public Understanding of Science 26, no. 6 (November 26, 2015): 721–37. http://dx.doi.org/10.1177/0963662515613702.

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This article presents a study of the content, use of sources and information sharing about climate change analysing over 60,000 tweets collected using a random week sample. We discuss the potential for studying Twitter as a communicative space that is rich in different types of information and presents both new challenges and opportunities. Our analysis combines automatic thematic analysis, semantic network analysis and text classification according to psychological process categories. We also consider the media ecology of tweets and the external web links that users shared. In terms of content, the network of topics uncovered presents a multidimensional discourse that accounts for complex causal links between climate change and its consequences. The media ecology analysis revealed a narrow set of sources with a major role played by traditional media and that emotionally arousing text was more likely to be shared.
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Simaki, Vasiliki, Eleni Seitanidi, and Carita Paradis. "Evaluating stance annotation of Twitter data." Research in Corpus Linguistics 11, no. 1 (2022): 53–80. http://dx.doi.org/10.32714/ricl.11.01.03.

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Taking stance towards any topic, event or idea is a common phenomenon on Twitter and social media in general. Twitter users express their opinions about different matters and assess other people’s opinions in various discursive ways. The identification and analysis of the linguistic ways that people use to take different stances leads to a better understanding of the language and user behaviour on Twitter. Stance is a multidimensional concept involving a broad range of related notions such as modality, evaluation and sentiment. In this study, we annotate data from Twitter using six notional stance categories ––contrariety, hypotheticality, necessity, prediction, source of knowledge and uncertainty––¬¬ following a comprehensive annotation protocol including inter-coder reliability measurements. The relatively low agreement between annotators highlighted the challenges that the task entailed, which made us question the inter-annotator agreement score as a reliable measurement of annotation quality of notional categories. The nature of the data, the difficulty of the stance annotation task and the type of stance categories are discussed, and potential solutions are suggested
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Gutiérrez Almazor, Miren, Maria J. Pando Canteli, and Mariluz Congosto. "New approaches to the propagation of the antifeminist backlash on Twitter." Investigaciones Feministas 11, no. 2 (June 14, 2020): 221–37. http://dx.doi.org/10.5209/infe.66089.

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A year after the #MeToo movement erupted, antifeminism started to retort. The idea behind the backlash was that ‘the men who have been accused are the heroes’ (Tolentino, 2018). Twitter was one of the public spaces where this confrontation occurred; the #HimToo backlash gathered steam in 2018 (Asimov, 2018) and expanded into 2019. Focussing on the reactions against #Cuéntalo Twitter campaign –the Spanish equivalent to #MeToo—, this article examines how the antifeminist backlash proliferates, offering a view of the dynamics driving it. The authors choose an eclectic and interdisciplinary approach that integrates graph theory and CDA (Critical Discourse Analysis), thus connecting social media formulations with offline discourses, and proposing new ways of studying social movements. To examine the backlash’s characteristics, this study utilises Congosto’s typology of Twitter profiles (Congosto, 2018). Findings suggest that both approaches are complementary and necessary, for while graph analysis enables the distinction of antifeminist communities on Twitter and their behaviour and characteristics, CDA allows investigators to uncover their discursive strategies and favoured themes.
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Mellon, Jonathan, and Christopher Prosser. "Twitter and Facebook are not representative of the general population: Political attitudes and demographics of British social media users." Research & Politics 4, no. 3 (July 2017): 205316801772000. http://dx.doi.org/10.1177/2053168017720008.

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A growing social science literature has used Twitter and Facebook to study political and social phenomena including for election forecasting and tracking political conversations. This research note uses a nationally representative probability sample of the British population to examine how Twitter and Facebook users differ from the general population in terms of demographics, political attitudes and political behaviour. We find that Twitter and Facebook users differ substantially from the general population on many politically relevant dimensions including vote choice, turnout, age, gender, and education. On average social media users are younger and better educated than non-users, and they are more liberal and pay more attention to politics. Despite paying more attention to politics, social media users are less likely to vote than non-users, but they are more likely to support the left leaning Labour Party when they do vote. However, we show that these apparent differences mostly arise due to the demographic composition of social media users. After controlling for age, gender, and education, no statistically significant differences arise between social media users and non-users on political attention, values or political behaviour.
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Baxter, Graeme, Rita Marcella, and Mary O'Shea. "Members of the Scottish Parliament on Twitter: good constituency men (and women)?" Aslib Journal of Information Management 68, no. 4 (July 18, 2016): 428–47. http://dx.doi.org/10.1108/ajim-02-2016-0010.

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Purpose – The purpose of this paper is to explore the use of Twitter by Members of the Scottish Parliament (MSPs) for the provision of constituency-related information, or in support of their constituency service work. Design/methodology/approach – Content analysis of 10,411 tweets sent by the 105 MSPs on Twitter during four weeks in early-2014. Findings – While there was some evidence of MSPs on Twitter acting as a promoter of local community interests and as a conduit for information on local policy issues and events, their tweets were dominated by the wider, national, political agenda and by the Scottish independence debate. Compared with their online behaviour as parliamentary candidates three years earlier, MSPs placed an even greater emphasis on the one-way broadcast of information to their followers. They were reluctant to respond to contentious local policy questions, or to enter into any visible, meaningful, political debate with their constituents. Research limitations/implications – Although the research was conducted seven months before the Scottish independence referendum on 18 September 2014, the independence debate still dominated proceedings on Twitter. It might, therefore, be appropriate to revisit MSPs’ use of Twitter at some point during a truer “peacetime” period. Originality/value – This is the first systematic content analysis of tweets sent by all MSPs on Twitter. It allows the authors to compare their actual Twitter use with that envisaged by the Scottish Parliament, as a way of MSPs communicating about their work and engaging with their constituents.
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Crocamo, Cristina, Marco Viviani, Francesco Bartoli, Giuseppe Carrà, and Gabriella Pasi. "Detecting Binge Drinking and Alcohol-Related Risky Behaviours from Twitter’s Users: An Exploratory Content- and Topology-Based Analysis." International Journal of Environmental Research and Public Health 17, no. 5 (February 26, 2020): 1510. http://dx.doi.org/10.3390/ijerph17051510.

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Binge Drinking (BD) is a common risky behaviour that people hardly report to healthcare professionals, although it is not uncommon to find, instead, personal communications related to alcohol-related behaviors on social media. By following a data-driven approach focusing on User-Generated Content, we aimed to detect potential binge drinkers through the investigation of their language and shared topics. First, we gathered Twitter threads quoting BD and alcohol-related behaviours, by considering unequivocal keywords, identified by experts, from previous evidence on BD. Subsequently, a random sample of the gathered tweets was manually labelled, and two supervised learning classifiers were trained on both linguistic and metadata features, to classify tweets of genuine unique users with respect to media, bot, and commercial accounts. Based on this classification, we observed that approximately 55% of the 1 million alcohol-related collected tweets was automatically identified as belonging to non-genuine users. A third classifier was then trained on a subset of manually labelled tweets among those previously identified as belonging to genuine accounts, to automatically identify potential binge drinkers based only on linguistic features. On average, users classified as binge drinkers were quite similar to the standard genuine Twitter users in our sample. Nonetheless, the analysis of social media contents of genuine users reporting risky behaviours remains a promising source for informed preventive programs.
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Srimulyo, Koko, and Achmad Halim P. "Information and source credibility towards information adoption amongst upper secondary school students." Jurnal Studi Komunikasi (Indonesian Journal of Communications Studies) 5, no. 1 (February 16, 2021): 74. http://dx.doi.org/10.25139/jsk.v5i1.3204.

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The purpose of this study was to determine the extent to which the information quality and source credibility affect the use and the process of information adoption, especially among upper secondary school students as Twitter users who are prone to hoaxes and fake news. Research subject and method: The stratified sample was 100 upper secondary school students in Surabaya who used Twitter and had read or followed threads. The respondents were asked questions to test their dependence on Twitter and their social media behaviour that affected the information adoption process. Information quality has a significant effect on usability, in contrast to source credibility which does not affect the usefulness of information; however, these two dependent variables have a strong relationship which intervenes in the information adoption process among upper secondary school students.
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Muthasima, Rochma, Surya Sumpeno, and Yoyon Kusnendar Suprapto. "Twitter Sentiment Analysis of Juvenile Behaviour Deviations using LSA (Latent Semantic Analysis)." Journal of Physics: Conference Series 1201 (May 2019): 012026. http://dx.doi.org/10.1088/1742-6596/1201/1/012026.

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Umit, Resul. "Strategic communication of EU affairs: an analysis of legislative behaviour on Twitter." Journal of Legislative Studies 23, no. 1 (January 2, 2017): 93–124. http://dx.doi.org/10.1080/13572334.2017.1283166.

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Rowe, Matthew, and Hassan Saif. "Mining Pro-ISIS Radicalisation Signals from Social Media Users." Proceedings of the International AAAI Conference on Web and Social Media 10, no. 1 (August 4, 2021): 329–38. http://dx.doi.org/10.1609/icwsm.v10i1.14716.

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The emergence and actions of the so-called Islamic State of Iraq and the Levant (ISIL/ISIS) has received widespread news coverage across the World, largely due to their capture of large swathes of land across Syria and Iraq, and the publishing of execution and propaganda videos. Enticed by such material published on social media and attracted to the cause of ISIS, there have been numerous reports of individuals from European countries (the United Kingdom and France in particular) moving to Syria and joining ISIS. In this paper our aim to understand what happens to Europe-based Twitter users before, during, and after they exhibit pro-ISIS behaviour (i.e. using pro-ISIS terms, sharing content from pro-ISIS accounts), characterising such behaviour as radicalisation signals. We adopt a data-mining oriented approach to computationally determine time points of activation (i.e. when users begin to adopt pro-ISIS behaviour), characterise divergent behaviour (both lexically and socially), and quantify influence dynamics as pro-ISIS terms are adopted. Our findings show that: (i) of 154K users examined only 727 exhibited signs of pro-ISIS behaviour and the vast majority of those 727 users became \emph{activated} with such behaviour during the summer of 2014 when ISIS shared many beheading videos online; (ii) users exhibit significant behaviour divergence around the time of their activation, and; (iii) social homophily has a strong bearing on the diffusion process of pro-ISIS terms through Twitter.
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Orduña-Malea, Enrique, Cristina I. Font-Julian, José Antonio Ontalba-Ruipérez, and Raúl Compés-López. "Masters of Wine on Twitter: presence, activity, impact and community structure." Wine Economics and Policy 10, no. 1 (April 14, 2021): 73–88. http://dx.doi.org/10.36253/wep-9055.

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Globalisation, the Internet and social media have changed the kind of actors with influence in the wine industry and the way these actors create signals to communicate credible information about experience and trust attributes. Among the most prestigious experts in the world of wine are the Masters of Wine (MW). Although initially devoted to international trade, they have spread their activities and their opinion is more and more appreciated by producers and consumers. The main objective of this article is to determine this community of experts’ behaviour on Twitter. In order to do so, four factors (presence, activity, impact and community) have been considered. All Twitter profiles belonging to users awarded with the MW qualification were identified and analysed. In addition, a set of 35,653 tweets published by the MWs were retrieved and analysed through descriptive statistics. The results show MWs on Twitter as high attractors (number of followers), moderate publishers (original contents published), moderate influencers (number of likes and retweets), and low interactors (number of friends and mentions to other users). These findings reveal that the MW community is not using Twitter to gain or reinforce their reputation as an accredited expert in the wine industry, giving more influential space on Twitter to consumers and amateurs.
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Salsabilla, Farah Pasha, and Dyah Rahmawati Hizbaron. "Understanding Community Collective Behaviour Through Social Media Responses: Case of Sunda Strait Tsunami, 2018, Indonesia." E3S Web of Conferences 325 (2021): 01021. http://dx.doi.org/10.1051/e3sconf/202132501021.

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The Sunda Strait Tsunami which occurred on 22nd December 2018 is one among too many examples of a rapid on-set disaster that attracted public attention through Twitter. This sudden event had a massive impact on parts of the west coast of Banten Province, Indonesia. Therefore, this research aimed to evaluate the collective response reflected on Twitter due to the 2018 Sunda Strait Tsunami. Previous studies shows the utilization of crowd sourcing data from social media for community capacity and quick assessment of disaster impacts. Therefore, the characteristics of people’s responses on social media based on spatio-temporal attributes needs to be understood first to build better understanding about the information that can be used for emergency response strategies consideration. This research method involved a spatial statistics approach, while data collection and descriptive analysis were carried out based on Twitter word cloud data. This analysis showed that temporally, the highest number of tweets was generated at the beginning of the disaster period with downward trend into the end of phase. As for spatially, people in directly affected areas by the disaster tend to give negative sentiments as their expression of sadness and fears towards the disaster. The content of the tweets involved asking for help, reporting on the current situation, and confirming the news on accounts belonging to government agencies. Furthermore, people in areas that were not directly affected produced tweets with more positive sentiment with expressions of condolences, sympathy, gratitude and invitations for volunteers and social actions.
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Gupta, Dr Deepa, and Dr Mukul Gupta. "A Study On Effect Of Social Media On Retail Buying Behaviour." Restaurant Business 118, no. 9 (September 25, 2019): 296–303. http://dx.doi.org/10.26643/rb.v118i9.8112.

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Retail is one of the major sectors in India seeking attention for the investment. It is also approaching a lot of foreign direct investment. An explosion of social media networks, in the last decade has erupted tradition information seeking in market. Social media such as Face book, twitter, you tube, Google has added a new social dimension to the web. This research paper is based on effect of social media on retail buying behaviour
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Gupta, Dr Deepa, Dr Mukul Gupta, and Dr Abhishek Singh. "A Study On Effect Of Social Media On Retail Buying Behaviour." Restaurant Business 118, no. 9 (September 27, 2019): 355–63. http://dx.doi.org/10.26643/rb.v118i9.8247.

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Retail is one of the major sectors in India seeking attention for the investment. It is also approaching a lot of foreign direct investment. An explosion of social media networks, in the last decade has erupted tradition information seeking in market. Social media such as Face book, twitter, you tube, Google has added a new social dimension to the web. This research paper is based on effect of social media on retail buying behaviour.
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Mahfud, Fakhris Khusnu Reza. "Sentiment Analysis of Perpustakaan Nasional Republik Indonesia Through Social Media Twitter." MATICS 12, no. 1 (April 7, 2020): 90. http://dx.doi.org/10.18860/mat.v12i1.8973.

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The library is a gate of science and a heart of civilization. Indonesia already has a Perpustakaan Nasional consisted of 27 floors and is equipped with facilities that are adequate for user needs. Apart from that, we need to see opinions from the community as users. Public opinion about the library is critical for library managers to evaluate services and facilities from the library. One way to find out the views of the community is by using social media twitter. Twitter social media is often used in channelling opinions or expressing opinions about specific topics; besides social media, twitter is commonly used for digital campaign movements. Submission of views and even digital campaigns on Twitter social media greatly influence the opinions and even behaviour of society in various ways. This study analyzes tweets about national libraries by classifying, positive opinions, negative opinions and neutral opinions. In this study, twitter data will go through the preprocessing, weighting, and classification stages. TF-IDF and TF binary are used in weighting in this study. The classification used in this study is Naive Bayes and KNN. Accuracy, precision, and recall values were also used in this study to evaluate classification performance. The highest classification performance using KNN classification with TF-IDF weighting resulted in the value of accuracy, precision, and recall of 83.33%, 79.2%, and 83.3% respectively.
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Pérez-López, Raúl, Raquel Gurrea-Sarasa, Carolina Herrando, María José Martín-De Hoyos, Victoria Bordonaba-Juste, and Ana Utrillas-Acerete. "The generation of student engagement as a cognition-affect-behaviour process in a Twitter learning experience." Australasian Journal of Educational Technology 36, no. 3 (June 29, 2020): 132–46. http://dx.doi.org/10.14742/ajet.5751.

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Twitter is a microblog that allows users to interact about a topic in online discussion. This makes it an interesting interactive tool with possibilities to increase student engagement and learning performance through active collaboration in an informal learning environment. However, few articles take a quantitative approach to investigate the creation of student engagement using this social networking site. To address this gap, we propose a series of activities conducted through Twitter to analyse the engagement generation process in a sample of 110 students in the first year of a business and administration degree at a large Spanish university. The results show that the engagement process is created through active collaborative learning and enjoyment, and that engaged students are more satisfied with the activity and perceive greater learning performance. This leads us to recommend teachers to encourage active and collaborative activities to make students more engaged and satisfied, and improve their performance.
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Mukunthan, B., and M. Arunkrishna. "Spam Detection and Spammer Behaviour Analysis in Twitter Using Content Based Filtering Approach." Journal of Physics: Conference Series 1817, no. 1 (March 1, 2021): 012014. http://dx.doi.org/10.1088/1742-6596/1817/1/012014.

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Llewellyn, Clare, Laura Cram, Robin L. Hill, and Adrian Favero. "For Whom the Bell Trolls: Shifting Troll Behaviour in the Twitter Brexit Debate." JCMS: Journal of Common Market Studies 57, no. 5 (June 11, 2019): 1148–64. http://dx.doi.org/10.1111/jcms.12882.

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Alabdullatif, Abdullatif, Basit Shahzad, and Esam Alwagait. "Classification of Arabic Twitter Users: A Study Based on User Behaviour and Interests." Mobile Information Systems 2016 (2016): 1–11. http://dx.doi.org/10.1155/2016/8315281.

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Social networks are among the most popular interactive media today due to their simplicity and their ability to break down the barriers of community rules and their speed and because of the increasing pressures of work environments that make it more difficult for people to visit or call friends. There are many social networking products available and they are widely used for social interaction. As the amount of threading data is growing, producing analysis from this large volume of communications is becoming increasingly difficult for public and private organisations. One of the important applications of this work is to determine the trends in social networks that depend on identifying relationships between members of a community. This is not a trivial task as it has numerous challenges. Information shared between social members does not have a formal data structure but is transmitted in the form of texts, emoticons, and multimedia. The inspiration for addressing this area is that if a company is advertising a sports product, for example, it has a difficulty in identifying targeted samples of Arab people on social networks who are interested in sports. In order to accomplish this, an experiment oriented approach is adopted in this study. A goal for this company is to discover users who have been interacting with other users who have the same interests, so they can receive the same type of message or advertisement. This information will help a company to determine how to develop advertisements based on Arab people’s interests. Examples of such work include the timely advertisement of the utilities that can be effectively marketed to increase the audience; for example, on the weekend days, the effective market approaches can yield considerable results in terms of increasing the sales and profits. In addition, finding an efficient way to recommend friends to a user based on interest similarity, celebrity degree, and online behaviour is of interest to social networks themselves. This problem is explored to establish and apply an efficient and easy way to classify a social network of Arab users based on their interests using available types of information, whether textual or nontextual, and to try to increase the accuracy of interest classification. Since most of the social networking is done from the mobiles nowadays, the efficient and reliable algorithm can help in developing a robust app that can perform the tweet classification on mobile phones.
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V, Sahana, Thanushree Gowda, and Vanishree S. "Statistical Analysis and Classification of Calamity Related Tweets." Recent Trends in Artificial Intelligence & it's Applications 1, no. 3 (October 5, 2022): 11–18. http://dx.doi.org/10.46610/rtaia.2022.v01i03.003.

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Twitter and other social media platforms have emerged as popular channels for communication during emergencies. Social networks generate huge amounts of data due to the behaviour of their users. A wide range of topics is discussed on social networks, including politics, health issues, and natural disasters. Therefore, public data provides a wealth of information on many topics. Traditional methods of communication have been enhanced in many ways by the Internet. In disaster assessment, Machine Learning (ML) and Artificial Intelligence (AI) algorithms are becoming increasingly popular. The use of micro blogging platforms such as Twitter during natural catastrophes and emergencies generates an increasing number of posts on these platforms. In this paper, we examine natural disasters, including avalanches, tornadoes, hurricanes, droughts, earthquakes, landslides, tsunamis, floods, volcanoes, and wildfires. We extract data from Twitter Network and classify them as disaster and non-disaster tweets as target and non-targets using SVM, Word2Vec, TFIDF, and BERT model.
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Mamic, Lilia Ivana, and Isidoro Arroyo Almaraz. "How the Larger Corporations Engage with Stakeholders through Twitter." International Journal of Market Research 55, no. 6 (November 2013): 851–72. http://dx.doi.org/10.2501/ijmr-2013-070.

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The digital era has revolutionised the traditional communication assumptions that we learned during past decades. Social media constitute the new communication challenge. Twitter has recently passed 517 million users. This study examines how some of the largest companies are making use of this popular microblogging site to engage with their stakeholders. Using content analysis, we coded 5,352 tweets. We analysed the tweet frequency, the followers and followings, friending behaviour, the retweets and public messages, and the use that companies are making of different communication tools provided by Twitter to augment the information shared on their tweets. The study found that corporations are not effectively employing the full interactivity potential this site offers to build mutually beneficial relationships with stakeholders. These findings call attention to some key interactivity features that organisations are failing to utilise.
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Zhou, J., F. Liu, and H. Zhou. "Understanding health food messages on Twitter for health literacy promotion." Perspectives in Public Health 138, no. 3 (March 7, 2018): 173–79. http://dx.doi.org/10.1177/1757913918760359.

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Aims: With the popularity of social media, Twitter has become an important tool to promote health literacy. However, many health-related messages on Twitter are dead-ended and cannot reach many people. This is unhelpful for health literacy promotion. This article aims to examine the features of online health food messages that people like to retweet. Methods: We adopted rumour theory as our theoretical foundation and extracted seven characteristics (i.e. emotional valence, attractiveness, sender’s authoritativeness, external evidence, argument length, hashtags, and direct messages). A total of 10,025 health-related messages on Twitter were collected, and 1496 messages were randomly selected for further analysis. Each message was treated as one unit and then coded. All the hypotheses were tested with logistic regression. Results: Emotional valence, attractiveness, sender’s authoritativeness, argument length, and direct messages in a Twitter message had positive effects on people’s retweet behaviour. The effect of external evidence was negative. Hashtags had no significant effect after consideration of other variables. Conclusion: Online health food messages containing positive emotions, including pictures, containing direct messages, having an authoritative sender, having longer arguments, or not containing external URLs are more likely to be retweeted. However, a message only containing positive or negative emotions or including direct messages without any support information will not be retweeted.
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Sundarrajan, Aksharaa, and M. Aneesha. "Survey on Detection of Metal Illnesses by Analysing Twitter Data." International Journal of Engineering & Technology 7, no. 2.24 (April 25, 2018): 37. http://dx.doi.org/10.14419/ijet.v7i2.24.11995.

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Mental illnesses are serious problems that places a burden on individuals, their families and on society in general. Although their symptoms have been known for several years, accurate and quick diagnoses remain a challenge. Inaccurate or delayed diagnoses results in increased frequency and severity of mood episodes, and reduces the benefits of treatment. In this survey paper, we review papers that leverage data from social media and design predictive models. These models utilize patterns of speech and life features of various subjects to determine the onset period of bipolar disorder. This is done by studying the patients, their behaviour, moods and sleeping patterns, and then effectively mapping these features to detect whether they are currently in a prodromal phase before a mood episode or not.
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Matosas López, Luis. "Variables of Twitter´s brand activity that influence audience spreading behaviour of branded content." ESIC Market Economics and Business Journal 49, no. 3 (September 1, 2018): 455–99. http://dx.doi.org/10.7200/esicm.161.0491.

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Karami, Amir, Vishal Shah, Reza Vaezi, and Amit Bansal. "Twitter speaks: A case of national disaster situational awareness." Journal of Information Science 46, no. 3 (March 4, 2019): 313–24. http://dx.doi.org/10.1177/0165551519828620.

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In recent years, we have been faced with a series of natural disasters causing a tremendous amount of financial, environmental and human losses. The unpredictable nature of natural disasters behaviour makes it hard to have a comprehensive situational awareness (SA) to support disaster management. Using opinion surveys is a traditional approach to analyse public concerns during natural disasters; however, this approach is limited, expensive and time-consuming. Luckily, the advent of social media has provided scholars with an alternative means of analysing public concerns. Social media enable users (people) to freely communicate their opinions and disperse information regarding current events including natural disasters. This research emphasises the value of social media analysis and proposes an analytical framework: Twitter Situational Awareness (TwiSA). This framework uses text mining methods including sentiment analysis and topic modelling to create a better SA for disaster preparedness, response and recovery. TwiSA has also effectively deployed on a large number of tweets and tracks the negative concerns of people during the 2015 South Carolina flood.
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Brena, Giovanni, Marco Brambilla, Stefano Ceri, Marco Di Giovanni, Francesco Pierri, and Giorgia Ramponi. "News Sharing User Behaviour on Twitter: A Comprehensive Data Collection of News Articles and Social Interactions." Proceedings of the International AAAI Conference on Web and Social Media 13 (July 6, 2019): 592–97. http://dx.doi.org/10.1609/icwsm.v13i01.3256.

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Online social media are changing the news industry and revolutionizing the traditional role of journalists and newspapers. In this scenario, investigating the behaviour of users in relationship to news sharing is relevant, as it provides means for understanding the impact of online news, their propagation within social communities, their impact on the formation of opinions, and also for effectively detecting individual stances relative to specific news or topics.Our contribution is two-fold. First, we build a robust pipeline for collecting datasets describing news sharing; the pipeline takes as input a list of news sources and generates a large collection of articles, of the accounts that provide them on the social media either directly or by retweeting, and of the social activities performed by these accounts. Second, we also provide a large-scale dataset, built using the aforementioned tool, that can be used to study the social behavior of Twitter users and their involvement in the dissemination of news items. Finally we show an application of our data collection in the context of political stance classification and we suggest other potential usages of the presented resources.
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