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《Information processing & management》2020,57(5):102220
Marketing professionals face challenges of increasing complexity to adapt classic marketing strategies to the phenomenon of social networks. Companies are currently trying to take advantage of the useful collective knowledge available on social networks to support different types of marketing decisions. The appropriate analysis of this information can offer marketing professionals with important competitive advantages. This work proposes a new methodology to extract the social collective behavior of Twitter users concerning a group of brands based on the users’ temporal activity. Time series of mentions made by individual users to each company’s Twitter account are aggregated to obtain collective activity data for the companies, which is a consequence of both the company’s and other users’ actions. These data are processed using classical unsupervised machine learning techniques, such as temporal clustering and hidden Markov models, to extract collective temporal behavior patterns and models of the dynamics of customers over time for a single brand and groups of brands. The derived knowledge can be used for different tasks, such as identifying the impact of a marketing campaign on Twitter and comparatively assessing the social behaviors of different brands and groups of brands to assist in making marketing decisions. Our methodology is validated in a case study from the wine market. Twitter data were gathered from four regions of different countries around the world with important wineries (Italy: Veneto, Portugal: Porto and Douro Valley, Spain: La Rioja, and United States: Napa Valley), and comparative behavior analysis was carried out from the perspective of the use of Twitter as a communication channel for marketing campaigns. 相似文献
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《Information processing & management》2022,59(1):102762
Business is based on manufacturing, purchasing, selling a product, and earning or making profits. Social media analytics collect and analyze data from various social networks such as Facebook, Instagram, and Twitter. Social media data analysis can help companies identify consumer desires and preferences, improve customer service and market analytics on social networks, and smarter product development and marketing investments. The business decision-making process is a step-by-step process that enables employees to resolve challenges by weighing evidence, evaluating possible solutions, and selecting a route. In this paper, Big Data-assisted Social Media Analytics for Business (BD-SMAB) Model increases awareness and affects decision-makers in marketing strategies. Companies can use big data analytics in many ways to enhance management. It can evaluate its competitors in real-time and change prices, make deals better than its competitors' sales, analyze competitors' unfavorable feedback and see if they can outperform that competitor. The proposed method examines social media analysis impacts on different areas such as real estate, organizations, and beauty trade fairs. This diversity of these companies shows the effects of social media and how positive decisions can be developed. Take better marketing decisions and develop a strategic approach. As a result, the BD-SMAB method enhance customer satisfaction and experience and develop brand awareness. 相似文献
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介绍了大数据概念、种类和特点,指出了图书馆已经具备了大数据基本特征,在递增的数据中快速地分析和挖掘出有价值信息并加以利用,是图书馆面临新课题和新的发展机遇。为此提出了图书馆借助应用大数据技术,逐步完善信息服务体系所必须采取的五项措施。 相似文献
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This paper investigates the research question if senders of large amounts of irrelevant or unsolicited information – commonly called “spammers” – distort the network structure of social networks. Two large social networks are analyzed, the first extracted from the Twitter discourse about a big telecommunication company, and the second obtained from three years of email communication of 200 managers working for a large multinational company. This work compares network robustness and the stability of centrality and interaction metrics, as well as the use of language, after removing spammers and the most and least connected nodes. The results show that spammers do not significantly alter the structure of the information-carrying network, for most of the social indicators. The authors additionally investigate the correlation between e-mail subject line and content by tracking language sentiment, emotionality, and complexity, addressing the cases where collecting email bodies is not permitted for privacy reasons. The findings extend the research about robustness and stability of social networks metrics, after the application of graph simplification strategies. The results have practical implication for network analysts and for those company managers who rely on network analytics (applied to company emails and social media data) to support their decision-making processes. 相似文献
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综合考虑生态设计与政府补贴，借助伊藤过程刻画动态变化的回收率，构建大数据服务商参与下的闭环供应链随机微分博弈模型，分析大数据服务商协助类型、服务费支付水平和政府补贴等参数对闭环供应链各成员决策和利润的影响。结果表明，所处环境不同时大数据服务商的最佳协助方式也不同；协助营销活动能有效刺激市场时，协助营销更能提升回收率、利润等；零售商和回收商合理分担大数据服务费可以促进闭环供应链的稳定；较回收补贴，生态设计补贴对零售价和批发价影响更显著，政府合理提高生态设计补贴更能提高闭环供应链整体利润。 相似文献
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小微企业对于我国经济和民生的发展具有重要意义，但总体存活率较低，又因其特殊的组织结构和管理方式，导致以大中型企业为研究对象的传统营销理论部分失灵。通过对653家中国新创小微企业的问卷调查数据，本研究从企业最关键的利益相关者──顾客的视角出发，采用结构方程模型和多重线性回归的方法实证检验了一个提升小微企业营销绩效的理论模型。研究发现：利用新创企业资产和实施顾客导向是小微企业增加营销绩效的两种有效途径，且新创企业资产比顾客导向对小微企业营销绩效影响更大。顾客认知合法性感知也对小微企业绩效具有显著积极影响，并在新创企业资产、顾客导向与小微企业营销绩效的关系中起中介作用。竞争强度负向调节了新创企业资产与顾客认知合法性感知的关系。 相似文献
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Reducing information asymmetry between investors and a firm can have an impact on the cost of equity, especially in an environment or times of uncertainty. New technologies can potentially help disseminate corporate financial information, reducing such asymmetries. In this paper we analyse firms’ dissemination decisions using Twitter, developing a comprehensive measure of the amount of financial information that a company makes available to investors (iDisc) from a big data of firms’ tweets (1,197,208 tweets). Using a sample of 4131 firm-year observations for 791 non-financial firms listed on the US NASDAQ stock exchange over the period 2009–2015, we find evidence that iDisc significantly reduces the cost of equity. These results are pronounced for less visible firms which are relatively small in size, have a low analyst following and a small number of investors. Highly visible firms are less likely to benefit from iDisc in influencing their cost of equity as other communication channels may have widely disseminated their financial information. Our investigations encourage managers to consider the benefits of directly spreading a firm’s financial information to stakeholders and potential investors using social media in order to reduce firm equity premium (COE). 相似文献
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以微信小程序为代表的轻量应用一定程度上改变了企业与用户之间的互动方式,如何提高“用户留存”已经成为企业进行社交媒体营销所面临的重要问题。在社交媒体情境下,小程序具有哪些特征、这些特征是否以及如何影响用户的持续使用意愿,并未得到理论界的足够重视。本研究从轻量化视角深入分析,基于信息系统成功模型与情绪理论构建了小程序轻量化特征影响用户持续使用意愿的理论模型。研究表明：信息-任务匹配、系统易用性以及服务响应性正向影响用户持续使用意愿;信息-任务匹配、服务响应性分别对用户积极情绪和流体验有促进作用,系统易用性正向影响用户流体验而对积极情绪的影响不显著;积极情绪分别在信息-任务匹配、服务响应性与用户持续使用意愿之间起到完全中介作用,流体验则完全中介了小程序轻量化特征与持续使用意愿之间的关系。研究构筑了“轻量化特征-情绪反应-行为意愿”完整的传导机制与影响路径,拓展了轻量应用持续使用、社交媒体用户情绪成因相关研究,结论对企业借助轻量应用进行社交媒体营销具有借鉴意义。 相似文献
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Journalists, emergency responders, and the general public use Twitter during disasters as an effective means to disseminate emergency information. However, there is a growing concern about the credibility of disaster tweets. This concern negatively influences Twitter users’ decisions about whether to retweet information, which can delay the dissemination of accurate—and sometimes essential—communications during a crisis. Although verifying information credibility is often a time-consuming task requiring considerable cognitive effort, researchers have yet to explore how people manage this task while using Twitter during disaster situations.To address this, we adopt the Heuristic-Systematic Model of information processing to understand how Twitter users make retweet decisions by categorizing tweet content as systematically processed information and a Twitter user’s profile as heuristically processed information. We then empirically examine tweet content and Twitter user profiles, as well as how they interact to verify the credibility of tweets collected during two disaster events: the 2011 Queensland floods, and the 2013 Colorado floods. Our empirical results suggest that using a Twitter profile as source-credibility information makes it easier for Twitter users to assess the credibility of disaster tweets. Our study also reveals that the Twitter user profile is a reliable source of credibility information and enhances our understanding of timely communication on Twitter during disasters. 相似文献
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[目的/意义]为了避免国内图书情报学界在大数据浪潮下走创新不守正的老路。[方法/过程]对情报学界开设大数据专业面临的挑战与冲击、情报学的学科根基、如何变革情报学研究与教育等问题进行深入分析。[结果/结论]如果不对现有师资队伍的知识结构进行调整,不对师资队伍的知识储备进行充实,情报学界培养出来的大数据人才将缺乏市场竞争力。大数据时代的情报学研究既要追求学科知识的严谨性,坚守研究内容与教学内容的相关性,也要理性地将大数据思维、大数据方法与技术融入情报学的学科知识体系。大数据时代的情报学教育应该保持学科边界的稳定性,保持内容结构的合理性。 相似文献
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老字号传统品牌正面临着当前市场和未来市场的抉择与挑战：“80后”、“90后”“新消费人群”以及未来消费人群正在离老字亏传统品牌而远去。老字号传统品牌如何应对抉择与挑战,实现传统品牌的传承与救赎？老字号传统品牌必须主动地研究市场,清醒认识市场,营销未来。实施文化营销、科技营销、时尚营销、电子商务营销策略和传统文化与国际元素的融合策略。让我们的“老字号”传统品牌,生于历史,活在当下,传承未来! 相似文献
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Although organizational factors related to big data analytics (BDA) and its performance have been studied extensively, the number of failed BDA projects continues to rise. The quality of BDA information is a commonly cited factor in explanations for such failures and could prove key to improving project performance. Using the resource-based view (RBV) lens, data analytics literature, business strategy control, and an empirical setup of two studies based on marketing and information technology managerial data, we draw on the dimensions of the balanced scorecard (BSC) as an integrating framework of BDA organizational factors. Specifically, we tested a model –from two different perspectives– that would explain information quality through analytical talent and organizations' data plan alignment. Results showed that both managers have a different understanding of what information quality is. The characteristics that make marketing a better informer of information quality are identified. In addition, hybrid (embedded) type analyst placements are seen to achieve better performance. Moreover, we add greater theoretical rigour by incorporating the moderating effect of the use of big data analytics in companies. Finally, the BSC provided a greater causal understanding of the resources and capabilities within a data strategy. 相似文献
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Using mobile devices for additional information search before, during and after watching television (either factual news or fictional TV series) - is an increasingly significant information management phenomenon. This activity has been recognised by both TV media executives and academia as ‘second screen’ activity. This paper develops and tests a ‘parasocial interaction-impulse buying’ - model that captures the behaviours of consumers watching a Chinese TV drama series. These audience-consumers were also engaging extensively (most on a daily basis) during the broadcast period with series related influencer social media activities on a second screen. A structural equation model was developed to analyse the data. Findings indicate that TV series audience consumers who are also highly engaged with influencer- consumer ‘second screen’ content are likely to experience positive narrative involvement leading to engagement in parasocial interaction behaviours and ultimately impulse buying behaviour. These findings have implications for managers by providing insights into (1) the effects of influencer second screen content (2) the processes by which consumers’ involvement in a TV show’s narrative leads to impulse buying of products. Thus, influencer related second screen consumer engagement should be considered a significant opportunity for marketers, as such activity makes consumers become more involved in the characters and the narrative of a particular TV show, leading to increased impulse buying. 相似文献
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Internet and social media offer firms novel ways of managing their marketing strategy and gain competitive advantage. The groups of users expressing themselves on the Internet about a particular topic, product, or brand are frequently called a virtual tribe or E-tribe. However, there are no automatic tools for identifying and studying the characteristics of these virtual tribes. Towards this aim, this paper presents Tribefinder, a system to reveal Twitter users’ tribal affiliations, by analyzing their tweets and language use. To show the potential of this instrument, we provide an example considering three specific tribal macro-categories: alternative realities, lifestyle, and recreation. In addition, we discuss the different characteristics of each identified tribe, in terms of use of language and social interaction metrics. Tribefinder illustrates the importance of adopting a new lens for studying virtual tribes, which is crucial for firms to properly design their marketing strategy, and for scholars to extend prior marketing research. 相似文献
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Remedios Melero 《Biochemia medica : ?asopis Hrvatskoga dru?tva medicinskih biokemi?ara / HDMB》2015,25(2):152-160
Emerging metrics based on article-level does not exclude traditional metrics based on citations to the journal, but complements them. Both can be employed in conjunction to offer a richer picture of an article use from immediate to long terms. Article-level metrics (ALM) is the result of the aggregation of different data sources and the collection of content from multiple social network services. Sources used for the aggregation can be broken down into five categories: usage, captures, mentions, social media and citations. Data sources depend on the tool, but they include classic metrics indicators based on citations, academic social networks (Mendeley, CiteULike, Delicious) and social media (Facebook, Twitter, blogs, or Youtube, among others). Altmetrics is not synonymous with alternative metrics. Altmetrics are normally early available and allow to assess the social impact of scholarly outputs, almost at the real time. This paper overviews briefly the meaning of altmetrics and describes some of the existing tools used to apply this new metrics: Public Library of Science - Article-Level Metrics, Altmetric, Impactstory and Plum.Key words: altmetrics, article-level metrics, citation, social media 相似文献
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移动互联网的发展为微博的发展提供了更加广阔的发展空间,以复杂网络的基本统计特性为基础,通过抓取新浪微博中的相关数据,对其进行处理分析,详细分析微博用户在信息发布行为、信息发布内容方面的相关特性以及用户的关注行为和评论转发行为进行了详细地分析,认为微博网络是典型的小世界网络,微博网络整体密度较小,呈稀疏状态,但局部密集;微博网络用户的分布呈不均匀的状态,用户在信息发布、分享等方面存在较大的信息不对称性,只有小部分用户拥有较多的信息资源,扮演核心角色,大部分用户在微博中处于边缘地位。这为微博营销和微博舆论引导与消解提供了基础。 相似文献
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《Information processing & management》2020,57(5):102261
People increasingly use Social Media (SM) platforms such as Twitter and Facebook during disasters and emergencies to post situational updates including reports of injured or dead people, infrastructure damage, requests of urgent needs, and the like. Information on SM comes in many forms, such as textual messages, images, and videos. Several studies have shown the utility of SM information for disaster response and management, which encouraged humanitarian organizations to start incorporating SM data sources into their workflows. However, several challenges prevent these organizations from using SM data for response efforts. These challenges include near-real-time information processing, information overload, information extraction, summarization, and verification of both textual and visual content. We highlight various applications and opportunities of SM multimodal data, latest advancements, current challenges, and future directions for the crisis informatics and other related research fields. 相似文献