ePADD: Computational Analysis Software Facilitating Screening, Browsing, and Access for Historically and Culturally Valuable Email Collections

Schneider, Josh; Chan, Peter; Edwards, Glynn; Hangal, Sudheendra

doi:10.1045/may2017-schneider

Cited by 2 publications

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“…Hangal, Lam, and Heer also reported anecdotal evidence that sentiment and name cues were highly evocative and allowed participants to recollect significant events in their lives. Although the sample size for the study was too small to be conclusive about the usefulness of these cues, modified and derived versions of MUSE have since been widely used to detect sentiments in e-mails (Hangal, Chan, Lam, & Heer, 2012;Nagpal, Hangal, Joyee, & Lam, 2012;Schneider, Chan, Edwards, & Hangal, 2017). In the present study, as is described in Table 1, we extracted sentiments corresponding to 15 categories of emotions, measured the occurrence of emoticons and exclamation points from the specific e-mail prompt, and also calculated the total sentiments in the e-mail document.…”

Section: Methodsmentioning

confidence: 99%

“…In addition to extracting sentiment features using MUSE, proper names mentioned in the sentences were extracted by a tokenizer using a derivative of MUSE, the Be-mail: Process, Appraise, Discover, and Deliver^(ePADD) named entity recognizer (Schneider et al, 2017), which excluded common Internet abbreviations (e.g., BTW, FYI), the participant's own name, and the recipient's name from the process. Other extracted features included but were not limited to the number of sentences, the length of the sentences, and the number of sent e-mails in a thread.…”

Section: Methodsmentioning

confidence: 99%

“…Furthermore, questions about the structure and scale of long-term memory (Moreton & Ward, 2010) could be answered through free recall paradigms based on easily verifiable, time-stamped e-mail events. Additionally, MUSE's algorithms for fetching and cleaning e-mail content, and using named entity recognition and other machine learning techniques to browse e-mail archives have been further developed to enable access and analysis of e-mails through ePADD (Schneider et al, 2017). ePADD empowers researchers to use preexisting e-mail collections to answer important research questions in a variety of domains.…”

Section: Future Directionsmentioning

confidence: 99%

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Autobiographical recall of personally familiar names and temporal information in e-mails: An automatic analytic approach using e-mail communications

2019

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An important question that arises from autobiographical memory research is whether the variables that influence memory in the laboratory also drive memory for autobiographical episodes in real life. We explored this question within the context of e-mail communications and investigated the variables that influence recall for personally familiar names and temporal information in emails. We designed a Web-based program that analyzed each participant's year-old sent e-mail archive and applied textual analysis algorithms to identify a set of sentences likely to be memorable. These sentences were then used as the stimuli in a cued recall task. Participants saw two sentences from their sent e-mail as a cue and attempted to recall the name of the e-mail recipient. Participants also rated the vividness of recall for the e-mail conversation and estimated the month in which they had written the e-mail. Linear mixed-effect analyses revealed that recipient name recall accuracy decreased with longer retention intervals and increased with greater frequency of contact with the recipient. Also, with longer retention intervals, participants dated e-mails as being more recent than their actual month. This telescoping error was moderately larger for e-mails with greater sentiment. These findings suggest that memory for personally familiar names and temporal information in e-mails closely follows the patterns for autobiographical memory and proper-name recall found in laboratory settings. This study introduces an innovative, Web-based experimental method for studying the cognitive processes related to autobiographical memories using ecologically valid, naturalistic communications.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Future Directionsmentioning

confidence: 99%

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Autobiographical recall of personally familiar names and temporal information in e-mails: An automatic analytic approach using e-mail communications

2019

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“…Visualisations, in particular, have regularly been employed as a method for exploring email collections and supporting the identification of high level patterns within a data-set (Louis and Engelbrecht 2011;Kaczmarek and West 2018;Moss et al 2018;Stadlinger and Dewald 2017). This practice is slowly migrating into the archival setting (Josh Schneider et al 2017) with the intention of supporting a holistic, creative, perhaps even 'playful' (Hendery and Burrell 2019) research.…”

Section: Introductionmentioning

confidence: 99%

A survey on email visualisation research to address the conflict between privacy and access

2022

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Emails, much like communicative genres such as letters that predate them, are a rich source of data for researchers, but they are replete with privacy considerations. This paper explores the resulting friction between privacy concerns and email data access. Studies of email can often be centred on understanding patterns of behaviour and/or relationships between people or groups, and, as such, embody risks of disclosing private information. This is further amplified in humanities research which is concerned with the individual, their work and the circumstances that influence them. Furthermore, previous studies have expounded upon the benefits of visualisations for researching email data, a method which has been reported both as a path to addressing known concerns, as well as, introducing new concerns in privacy. The spectrum of methodologies leave archivists and curators of email data in a quandary, unable to balance accessibility with privacy. The research presented in this paper contributes a systematic approach to examining the relationship between email visualisation research and privacy. It presents a categorisation of email visualisation attributes, and a graded scale of privacy, to be used in conjunction as a framework for interrogating existing research and their associated email collections. The paper aims to instigate the first steps in concretely situating the extent to which research can take advantage of or is challenged by privacy conscious data management.

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ePADD: Computational Analysis Software Facilitating Screening, Browsing, and Access for Historically and Culturally Valuable Email Collections

Cited by 2 publications

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Autobiographical recall of personally familiar names and temporal information in e-mails: An automatic analytic approach using e-mail communications

Autobiographical recall of personally familiar names and temporal information in e-mails: An automatic analytic approach using e-mail communications

A survey on email visualisation research to address the conflict between privacy and access

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