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In this research, we evaluate the effect of gender targeted advertising on the performance of sponsored search advertising. We analyze nearly 7,000,000 records spanning 33 consecutive months of a keyword advertising campaign from a major US retailer. In order to determine the effect of demographic targeting, we classify the campaign’s key phrases by a probability of being targeted for a specific gender, and we then compare the key performance indicators among these groupings using the critical sponsored search metrics of impressions, clicks, cost-per-click, sales revenue, orders, and items, and return on advertising. Findings from our research show that the gender-orientation of the key phrase is a significant determinant in predicting behaviors and performance, with statistically different consumer behaviors for all attributes as the probability of a male or female keyword phrase changes. However, gender neutral phrases perform the best overall, generating 20 times the return of advertising than any gender targeted category. Insight from this research could result in sponsored advertising efforts being more effectively targeted to searchers and potential consumers. 相似文献
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关键词检索特性的计量学分析 总被引：1，自引：0，他引：1
利用文献计量学方法,对关键词检索文献出现的数量上特征,通过列表进行分析,得出关键词检索具有专指性、结合性与层次性以及层次性分离的特性,形成对关键词检索的认识,对标引与检索文献以及日后的研究具有积极意义。 相似文献
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Bernard J. Jansen Zhe Liu Courtney Weaver Gerry Campbell Matthew Gregg 《Information processing & management》2011
Real time search is an increasingly important area of information seeking on the Web. In this research, we analyze 1,005,296 user interactions with a real time search engine over a 190 day period. Using query log analysis, we investigate searching behavior, categorize search topics, and measure the economic value of this real time search stream. We examine aggregate usage of the search engine, including number of users, queries, and terms. We then classify queries into subject categories using the Google Directory topical hierarchy. We next estimate the economic value of the real time search traffic using the Google AdWords keyword advertising platform. Results shows that 30% of the queries were unique (used only once in the entire dataset), which is low compared to traditional Web searching. Also, 60% of the search traffic comes from the search engine’s application program interface, indicating that real time search is heavily leveraged by other applications. There are many repeated queries over time via these application program interfaces, perhaps indicating both long term interest in a topic and the polling nature of real time queries. Concerning search topics, the most used terms dealt with technology, entertainment, and politics, reflecting both the temporal nature of the queries and, perhaps, an early adopter user-based. However, 36% of the queries indicate some geographical affinity, pointing to a location-based aspect to real time search. In terms of economic value, we calculate this real time search stream to be worth approximately US $33,000,000 (US $33 M) on the online advertising market at the time of the study. We discuss the implications for search engines and content providers as real time content increasingly enters the main stream as an information source. 相似文献
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Sponsored search is an online advertising channel that has gained momentum worldwide. The key challenge is deciding on the types of keywords to bid on and matching options to utilise for the keywords. In this paper, we address this problem by providing a broad analysis on how the various traffic search metrics (length, CTR, average cost per click (CPC), average position, and quality score) influence the bidding results as the keyword matching option becomes broader, that is, from exact, to phrase to broad. Drawing on the shopping goals theory, we also establish the profile of the metrics associated with a more focused search intent across the matching options. Using a random sample of keywords selected from 9 640 keywords that online advertisers have bid on, spanning a variety of markets, the results indicate that as the matching option becomes narrower, that is, from broad to exact, the keyword traffic metrics increase in general, except for cost, which does not differ significantly across the matching options. Longer keywords, which are typically associated with a more focussed search intent, generate more clicks and have a higher quality measure on average across all matching options. The longer keywords are cheaper for the exact match option, but more expensive for the other matching options. The results are inconclusive with regard to the position that longer keywords occupy on a results page across the matching options. Thus, the narrower matching options and longer keywords matching those that a customer would typically use to search for a company's goods and services need to be targeted to ensure higher visits to a company's website. 相似文献
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[目的/意义]旨在为提高虚拟社区在应急管理中的作用提供参考。[方法/过程]以Web of Science为数据源,通过关键词搜索获取近五年的相关文献,利用VOSviewer进行关键词共现分析,结合内容分析对国际上虚拟社区在应急管理中的应用研究热点内容进行梳理,并进行总结和展望。[结果/结论]该主题领域的研究具有较强的学科综合性,虚拟社区内容挖掘技术与方法的研究、危机信息交流行为、融合了虚拟社区的系统理论框架构建与系统平台开发研究是目前学者关注的重点。 相似文献
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《Information processing & management》2022,59(2):102853
Predicting the probability that a user will click on a specific advertisement has been a prevalent issue in online advertising, attracting much research attention in the past decades. As a hot research frontier driven by industrial needs, recent years have witnessed more and more novel learning models employed to improve advertising CTR prediction. Although extant research provides necessary details on algorithmic design for addressing a variety of specific problems in advertising CTR prediction, the methodological evolution and connections between modeling frameworks are precluded. However, to the best of our knowledge, there are few comprehensive surveys on this topic. We make a systematic literature review on state-of-the-art and latest CTR prediction research, with a special focus on modeling frameworks. Specifically, we give a classification of state-of-the-art CTR prediction models in the extant literature, within which basic modeling frameworks and their extensions, advantages and disadvantages, and performance assessment for CTR prediction are presented. Moreover, we summarize CTR prediction models with respect to the complexity and the order of feature interactions, and performance comparisons on various datasets. Furthermore, we identify current research trends, main challenges and potential future directions worthy of further explorations. This review is expected to provide fundamental knowledge and efficient entry points for IS and marketing scholars who want to engage in this area. 相似文献
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文章以中国期刊全文数据库（CNKI）为数据源,以发表在CSSCI和核心期刊的2004-2013年有关开放存取的507篇文献为研究对象,对其进行年代分析,研究发现：2004-2008年开放存取研究呈现迅猛增长趋势,2009-2013年开放存取的研究趋势平稳,因此文章将开放存取的发展分为2个阶段,即开放存取研究的第一个阶段（2004-2008年）、开放存取研究的第二个阶段（2009-2013年）。利用关键词共现分析方法分析我国开放存取在每个阶段的研究热点,并采用社会网络分析方法分析开放存取文献的高产作者,以透析国内开放存取领域的研究热点和作者合作团体,从多方面揭示国内开放存取的发展现状和研究趋势。 相似文献
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Since an ever-increasing part of the population makes use of social media in their day-to-day lives, social media data is being analysed in many different disciplines. The social media analytics process involves four distinct steps, data discovery, collection, preparation, and analysis. While there is a great deal of literature on the challenges and difficulties involving specific data analysis methods, there hardly exists research on the stages of data discovery, collection, and preparation. To address this gap, we conducted an extended and structured literature analysis through which we identified challenges addressed and solutions proposed. The literature search revealed that the volume of data was most often cited as a challenge by researchers. In contrast, other categories have received less attention. Based on the results of the literature search, we discuss the most important challenges for researchers and present potential solutions. The findings are used to extend an existing framework on social media analytics. The article provides benefits for researchers and practitioners who wish to collect and analyse social media data. 相似文献
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[目的/意义]近半个世纪以来,研究者在信息查询系统分面导航的设计和评价中积累了丰富的研究成果,但这些成果却一直处于分散杂乱状态,不能很好地指导信息查询系统的设计。[方法/过程]本文采用文献调查法和文献分析法,根据影响信息查询系统可用性的情境框架,从系统、任务、用户等方面对这些成果进行分析综合。[结果/结论]由此组织成一个支持信息查询系统分面导航设计的知识体系并就其设计提出相关建议。 相似文献
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研究热点反映出某一学科或领域的研究行为在特定时期的偏好，这种偏好的出现与那个“当下”的历史整体性紧密相关。本文采用文献计量学方法，选择CSSCI数据库中1998—2015年间收录的广告学论文为研究对象，在Citespace 软件辅助下绘制关键词共现图谱、时区知识演化视图。从30个高频关键词中筛选出6个高中介中心度和强突现的词汇，据此分析我国该阶段广告学科的研究热点和趋势。同时，相关学者与文献介入到以上关键词盛行的社会和历史现场，使得广告学研究活动与宏观社会历史背景发生关联。研究结果表明，由特定社会情境引发的广告业界前沿议题直接影响了学界的研究热点及偏向。而从更为广泛的意义上说，广告学研究重应用、轻理论的状况没有发生根本性转变。 相似文献
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鉴于传统方法对科研成果关键词研究存在较强主观影响和较少考虑时间因素等问题,提出基于时间序列聚类的科研成果关键词分析方法。该方法通过统计分析方法验证关键词出现顺序在一定程度上反映了关键词反映主题思想的重要性,将关键词的重要度转化为时间序列数据,分别从重要度的数值和趋势两个角度出发,使用动态时间弯曲方法度量关键词重要度时间序列数据之间的相似性,结合近邻传播方法对关键词时间序列数据之间的相似性矩阵进行聚类分析,实现科研成果的关键词分析研究。通过对某科研管理类重要期刊2008—2017年期间刊发的科研成果论文关键词研究发现：新方法不仅可以对科研成果中关键词的关注热度和趋势进行聚类划分,自适应地找到中心关键词作为相应类别的特征代表对象,还能为科研成果关键词的主题分析提供理论方法和决策支持。 相似文献
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科技查新检索中的关键词选择 总被引：12，自引：0，他引：12
科技查新检索不同于一般文献检索,查新检索者要针对课题的查新点检索一系列的文献数据库,并对以此出具的查新报告的客观性、公正性承担法律责任。在浩如烟海的国内外文献中针对特定检索课题力求做到查准、查全并非易事,单就检索过程中的关键词选择就往往令人困惑!科技文献中普遍存在的一物多名（或同义词）是查新检索中的永恒难题。为了尽量减少漏检,查新者应对检索用关键词进行扩展,并以适当的检索策略覆盖关键词表达的盲区,必要时还应采用分类法检索作为主题法检索的补充,通过多种途径设法化解一物多名给科技文献资源共享带来的难题!科技查新本身是一种创造性的劳动。查新者应充满自信地敞开思路,用创造性的思维,深入自如地施展文献检索才艺。 相似文献
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Kai Hu Qing Luo Kunlun Qi Siluo Yang Jin Mao Xiaokang Fu Jie Zheng Huayi Wu Ya Guo Qibing Zhu 《Information processing & management》2019,56(4):1185-1203
Topic evolution has been described by many approaches from a macro level to a detail level, by extracting topic dynamics from text in literature and other media types. However, why the evolution happens is less studied. In this paper, we focus on whether and how the keyword semantics can invoke or affect the topic evolution. We assume that the semantic relatedness among the keywords can affect topic popularity during literature surveying and citing process, thus invoking evolution. However, the assumption is needed to be confirmed in an approach that fully considers the semantic interactions among topics. Traditional topic evolution analyses in scientometric domains cannot provide such support because of using limited semantic meanings. To address this problem, we apply the Google Word2Vec, a deep learning language model, to enhance the keywords with more complete semantic information. We further develop the semantic space as an urban geographic space. We analyze the topic evolution geographically using the measures of spatial autocorrelation, as if keywords are the changing lands in an evolving city. The keyword citations (keyword citation counts one when the paper containing this keyword obtains a citation) are used as an indicator of keyword popularity. Using the bibliographical datasets of the geographical natural hazard field, experimental results demonstrate that in some local areas, the popularity of keywords is affecting that of the surrounding keywords. However, there are no significant impacts on the evolution of all keywords. The spatial autocorrelation analysis identifies the interaction patterns (including High-High leading, High-Low suppressing) among the keywords in local areas. This approach can be regarded as an analyzing framework borrowed from geospatial modeling. Moreover, the prediction results in local areas are demonstrated to be more accurate if considering the spatial autocorrelations. 相似文献
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通过全面分析人工智能技术在国际知识管理领域中的应用,了解目前该领域的主要研究主体、热点主题、高影响力文献,并推测今后的研究方向。选取Web of Science 作为数据来源,对检索得到的388篇论文通过可视化软件CiteSpace和VOSviewer从年代分布、关键词、文献共被引、期刊叠加等方面进行统计分析。结果显示,文本挖掘、嵌入性、认知计算、故障管理等是该研究领域的前沿热点。大数据、平衡核心卡、临床决策支持认知计算等可能是今后研究的新热点。同时,识别得到了该领域活跃的研究主体、高影响力文献及期刊的学科分布领域。 相似文献
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The popularity of mobile devices has ushered in the prosperity of mobile commerce, yet research on mobile advertising and mobile marketing remains scant. Marketing ads possessing higher media richness generally have a positive effect on consumer decision-making, because rich media conveys more information, but mobile ads with richer media imply higher costs for both the marketer and the audience. The limitations of mobile devices have further highlighted the difficulty of mobile advertising and the issue of advertising costs. Selecting which media to deliver the appropriate information is the latest research trend, but few studies have applied the media richness theory to explain mobile ads’ effect on consumer behavior. This research thus explores the impact of media richness on consumer behavior at different AISAS (attention, interest, search, action, and share) stages, adopting experimental research, convenient sampling, and online questionnaire to collect data. From a total of 424 valid questionnaires, we find that media richness has a greater influence on the three early stages of AIS while having a lower impact on the later stages of AS. This research thus suggests that firms employing mobile ads should choose high richness media for those potential customers who are at the early stage of consumer behavior (AIS). For those who at the later stage (AS), it is good enough for marketers to utilize medium richness mobile ads. Following this suggestion, marketers can place mobile ads more precisely, thus improving the likelihood of a reduction in advertising costs for both the marketer and audience. As mobile ads with high media richness are more effective for high perceived risk products, firms need to use high richness media when they are promoting high perceived risk products even when potential consumers are at the later stage of AS. This research contributes to marketers dedicated to using a mobile advertisement strategy and helps refine both online consumer behavior and the media richness theory when including the context of mobile commerce. 相似文献
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[目的/意义]查询式搜索适用于目标明确的提问应答式信息问题，探索式搜索更注重搜索过程的人机交互性、动态性与多面性，两者表现出不同的行为特征。作为搜索行为研究的基本问题之一，相关研究还比较缺乏。论文旨在探究查询式搜索与探索式搜索行为特征的差异，这对于信息搜索系统的功能优化以及指导用户高效获取信息都具有重要的实践意义。[方法/过程]论文以健康信息搜索为例，采用搜索行为实验的方法，通过对录屏数据的分析，从检索策略、学习行为、深度搜索和搜索绩效4个维度对两种搜索行为进行比较。[结果/结论]查询式搜索与探索式搜索在关键词变换数、访问网页数目等6个指标上存在显著性差异，在检索工具选择、查询串长度、搜索结果集的翻页和相关链接搜索4个指标上不存在显著性差异。 相似文献
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Mohsen JahangirianAuthor Vitae Tillal EldabiAuthor Vitae 《International Journal of Information Management》2011,31(3):234-243
While literature reviews with a large-scale scope are nowadays becoming a staple element of modern research practice, there are many challenges in taking on such an endeavour, yet little evidence of previous studies addressing these challenges exists. This paper introduces a practical and efficient review framework for extremely large corpora of literature, refined by five parallel implementations within a multi-disciplinary project aiming to map out the research and practice landscape of modelling, simulation, and management methods, spanning a variety of sectors of application where such methods have made a significant impact. Centred on searching and screening techniques along with the use of some emerging IT-assisted analytic and visualisation tools, the proposed framework consists of four key methodological elements to deal with the scale of the reviews, namely: (a) an incremental and iterative review structure, (b) a 3-stage screening phase including filtering, sampling and sifting, (c) use of visualisation tools, and (d) reference chasing (both forward and backward). Five parallel implementations of systematically conducted literature search and screening yielded a total initial search result of 146 087 papers, ultimately narrowed down to a final set of 1383 papers which was manageable within the limited time and other constraints of this research work. 相似文献