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The success of e-retailers is intrinsically linked to the effectiveness of their logistics processes which, inevitably, involve third party service providers. As the most tangible representative of the e-retailers it is inevitable that customers expect the e-retailer to resolve delivery queries, including on social media platforms. The purpose of this paper is to investigate the effectiveness of e-retailers’ logistics-related customer service interactions on Twitter with a view towards identifying effective and ineffective social media customer service strategies.

The design and public nature of Twitter encourages organic conversations between e-retailers and customers as well as between customers and other customers. The methodology applied here accounts for this by collecting and analysing interactions within and as part of conversations, not as independent observations. In total, 203,349 tweets were collected from 22 of the most popular e-retailers. A random sample of 5,000 logistics-related conversations (16,998 tweets) is used for the analysis presented here and forms a foundation for future research.

Conversations are initiated by customers on the basis of 24 event triggers which can be categorised as occurring either before or after an order is delivered. These can be general queries or related to a specific order or delivery issue. The paper identifies a number of significant findings such as the extent to which e-retailers and logistics providers redirect customers to other channels to resolve queries, ignoring the implicit preference by customers to use Twitter to resolve their problem. Similarly, the lack of interactions between e-retailers and their logistics providers within the Twitter platform to help resolve customer queries results in ineffective customer service.

The study identifies the way in which e-retailers can substantially improve the effectiveness of the customer service they provide on Twitter by ensuring that customer queries can be resolved within the platform and by working with their logistics partners to do the same. This is critical since problems may be directed to the e-retailer or the logistics provider but both companies jointly suffer the consequences of poor customer service.

The study examines a hitherto underexplored aspect of retail logistics – the social media-based customer service activities of e-retailers. Methodologically, the study is rooted in the acknowledgement that interactions on Twitter form conversations and analyses should take this into account. This is a distinctly different approach from existing Twitter-related studies which conduct an automated sentiment analysis of tweets. This approach reveals a rich picture of interactions and, importantly, identifies where conversations between e-retailers begin, how they develop and how they conclude.

Academic librarians have often been hesitant to foreground real-time engagement with social justice in our public facing library guides. The guides, more often than not, serve merely to provide access points to “academic” materials and traditional news sources. Perhaps there is a different path. This chapter suggests that engagement with Twitter can point patrons toward the real conversations happening outside (and sometimes inside) academia that are missed when we rely on traditional sources. The critical engagement with social justice issues such as race and technology, or migrant justice, is happening right in front of our eyes on Twitter. This chapter discusses how adding Twitter feeds to library guides can engage libraries (and our students) in critical conversations around racism and the foregrounding of traditionally marginalized voices. A problem with traditional library guides is that they center the voice and opinion of the librarian curating the guide. Adding in Twitter feeds can complicate this. Adding Twitter feeds from traditionally marginalized voices centers those voices in real time as opposed to centering the voice and authority of the, often white, librarian initially creating the guide. This centering occurs because while the librarian initially chooses which feeds to feature, the feeds are continuously updating in real time. This chapter reflects on why this centering of non-white voices is important, how it engages the counterpublic discourse on Twitter, and how doing so can push us all to be a little more critical, a little more subversive, in our work.

The purpose of this paper is to investigate practices of argumentation on Twitter discussions about climate change.

Conversational threads were collected from the Twitter API. Fundamental concepts from argumentation theory and linking practices were operationalised through a coding schema for content analysis. Tweets were analysed in the context of the discussions and coded according to their argumentative approach, interaction type and argumentation stage. Linked and embedded sources were analysed in order to find how they were used in arguments, the plausibility and soundness of the message, the consistency and trustworthiness of the linked source and its adequacy with the target audience.

Among the interactions between arguers, this study found five typical practices and several patterns involving the dynamics of the conversations, the strategy of the argumentation and the linking practices. Although the rhetorical approach was prominent, the agreement was rarely achieved. The arguers used a variety of sources to justify or support their positions, often embedding non-textual content. These linking practices, together with the strategy adopted and the topics discussed, suggest the involvement of a multiple audience engaged in discussing ad lib scientific artefacts, topics and outputs.

While Twitter has been the focus for many research papers, the conversational threads have been given little attention so far. With the Twitter API making conversations more accessible for research, this paper does not only give insight into multiple audience group argumentation dynamics but also provides a method to study the conversations from an argumentation theory perspective.

The job market for communication majors increasingly expects those graduating in these specializations to not only know how to create strategic plans for using social media in both one-way and two-way communication environments, but also maintain proper social media etiquette and virtual culture norms for their clients. To better prepare students for this expectation, two faculty members at separate universities designed and implemented a course assignment intended to promote cross-university collaboration, foster discussion, and bring students to use microblogging via Twitter. This assignment was designed so that it would not only have the students construct the meaning and best practices in a social setting using social media, but also encourage them to experience Twitter from a user perspective while building relationships in a manner that their future employers may have to work with their publics or customers. Overall, the educators involved in this project did feel that it was a beneficial assignment for students in both classes. While the students may not appreciate the assignment while it is being conducted, many of them have expressed the value in it now that the assignment is completed.

This study is motivated to provide a theoretically informed, data-driven assessment of the consequences associated with the participation of non-human bots in social accountability movements; specifically, the anti-inequality/anti-corporate #OccupyWallStreet conversation stream on Twitter.

A latent Dirichlet allocation (LDA) topic modeling approach as well as XGBoost machine learning algorithms are applied to a dataset of 9.2 million #OccupyWallStreet tweets in order to analyze not only how the speech patterns of bots differ from other participants but also how bot participation impacts the trajectory of the aggregate social accountability conversation stream. The authors consider two research questions: (1) do bots speak differently than non-bots and (2) does bot participation influence the conversation stream.

The results indicate that bots do speak differently than non-bots and that bots exert both weak form and strong form influence. Bots also steadily become more prevalent. At the same time, the results show that bots also learn from and adapt their speaking patterns to emphasize the topics that are important to non-bots and that non-bots continue to speak about their initial topics.

These findings help improve understanding of the consequences of bot participation within social media-based democratic dialogic processes. The analyses also raise important questions about the increasing importance of apparently nonhuman actors within different spheres of social life.

The current study is the first, to the authors’ knowledge, that uses a theoretically informed Big Data approach to simultaneously consider the micro details and aggregate consequences of bot participation within social media-based dialogic social accountability processes.

The purpose of this paper is to describe and analyse relationships and communication between Twitter actors in Swedish political conversations. More specifically, the paper aims to identify the most prominent actors, among these actors identify the sub-groups of actors with similar political affiliations, and describe and analyse the relationships and communication between these sub-groups.

Data were collected during four weeks in September 2012, using Twitter API. The material included 77,436 tweets from 10,294 Twitter actors containing the hashtag #svpol. In total, 916 prominent actors were identified and categorised according to the main political blocks, using information from their profiles. Social network analysis was utilised to map the relationships and the communication between these actors.

There was a marked dominance of the three main political blocks among the 916 most prominent actors: left block, centre-right block, and right-wing block. The results from the social network analysis suggest that while polarisation exists in both followership and re-tweet networks, actors follow and re-tweet actors from other groups. The mention network did not show any signs of polarisation. The blocks differed from each other with the right-wingers being tighter and far more active, but also more distant from the others in the followership network.

While a few papers have studied political polarisation on Twitter, this is the first to study the phenomenon using followership data, mention data, and re-tweet data.

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.

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.

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.

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.

The purpose of this paper is to explore the analysis of the potential contribution of festivals in generating a destination image through social media (particularly Twitter).

This study follows a multi-method approach by recollecting, analyzing and mixing quantitative and qualitative techniques. The authors focus on the case of Vic (Spain), analyzing the destination’s image as projected by different users (administration, private sector, particular users, residents) on Twitter in relation to an international musical festival, El Mercat de Música Viva de Vic (the Vic Live Music Market).

From a theoretical perspective, the study’s results advocate a reconsideration of the role of social media in the processes of creating a destination’s image. It is important to take into account the need to perform a specific analysis for each platform and consider how it operates and which stakeholders prevail by weight, by the clusters they pertain to and by their elicited descriptions. In the particular case of Twitter, the image-formation continuum generated by different actors through different sources is present here on one single platform.

This study is limited in terms of being based on only one social media site, and it would be very interesting to complement it by analyzing other relevant social media platforms.

From a practical point of view, this presents a challenge to destination managers to learn how to work on each specific platform in order to oversee the different destination visions and their resources.

From the results, the authors affirm that destination-branding analyses now need a platform-specific approach as well as an in-depth stakeholder analysis, since it is no longer possible to separate producers and consumers in brand image creation. Branding is becoming a more inclusive and collaborative process.

The purpose of the paper is to analyse the interactions of bridging users in Twitter discussions about vaccination.

Conversational threads were collected through filtering the Twitter stream using keywords and the most active participants in the conversations. Following data collection and anonymisation of tweets and user profiles, a retweet network was created to find users bridging the main clusters. Four conversations were selected, ranging from 456 to 1,983 tweets long, and then analysed through content analysis.

Although different opinions met in the discussions, a consensus was rarely built. Many sub-threads involved insults and criticism, and participants seemed not interested in shifting their positions. However, examples of reasoned discussions were also found.

The study analyses conversations on Twitter, which is rarely studied. The focus on the interactions of bridging users adds to the uniqueness of the paper.

The purpose of this paper is to develop a measurement scale for assessing the quality of dialogic conversations among companies and digital publics in social media. Dialogic conversations are defined as sequences of communicative actions and counteractions taken by social actors for different purposes based on specific linguistic choices and characterised by diverse communicative approaches and the role played by the involved parties.

A multidimensional scale for measuring dialogic conversations is developed from relevant literature concerning dialogue and public engagement in the fields of corporate communication, public relations, management studies and conversation analysis. The scale is built on three main dimensions: organisation turn-taking, sequencing of conversation, repair strategies and procedures. A pilot study was conducted to purify it from irrelevant variables.

Results of the pilot study show a general good level of reliability for the majority of the proposed variables for Facebook but not for Twitter. This may indicate that Facebook is a more dialogical forum than Twitter.

This is the first study proposing a systematic measurement of the dialogue orientation of online conversations that takes into consideration the role of language and communicative actions. The proposed measurement offers corporate communication managers a concrete tool for evaluating the quality of their online communications and for identifying those areas of their online communication that need improvement.