The Enron Corpus: A New Dataset for Email Classification Research

By Bryan Klimt, Yiming Yang. 2004

784 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Information Systems

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Citations in the corpus

Privacy Amplification by Iteration (2018, background): “The public corpus can be based on optin population, such as a product’s developers or early testers, data shared by volunteers [12], or be released through a legal process [13].”
This Email Could Save Your Life: Introducing the Task of Email Subject Line Generation (2019, methodology): “To introduce the task, we build the ﬁrst dataset, Annotated Enron Subject Line Corpus (AESLC), by leveraging the Enron Corpus (Klimt and Yang, 2004)”
What Does it Mean for a Language Model to Preserve Privacy? (2022, background): “It is not enough to claim privacy is preserved because attacks are not able to An employee at Enron [48] shares their wife’s social security number (who is not part of the company) for the purpose of setting up insurance.”
An extensive experimental comparison of methods for multi-label learning (2012, background): “Enron [33] is a dataset that contains the e-mails from 150 senior Enron officials.”
DynGEM: Deep Embedding Method for Dynamic Graphs (2018, background): “ENRON [ Klimt and Yang, 2004 ] : The dataset contains emails between employees in Enron Inc. from Jan 1999 to July 2002.”
Toward link predictability of complex networks (2015, background): “We consider the following 10 real-world networks drawn from disparate fields: ( i ) Jazz (37), a collaboration network of jazz musicians consists of 198 nodes and 2742 interactions; ( ii ) Metabolic (38), the metabolic network of Caenorhabditis elegans ; ( iii ) Neural (32), the neural network of C.”
A survey of the applications of text mining in financial domain (2016, methodology): “Various Studies of Phishing Detection Study Dataset Model Performance Measure Abdelhamid et al. (2014) Millersmiles/ PhishTank Associative Rule Accuracy Chen et al. (2011) Millersmiles DT/ NN/ SVM Accuracy He et al. (2011) Millersmiles\ PhishTank\ 3Sharp SVM True Positive/ False Positive Aburrous et”
AWQ: Activation-aware Weight Quantization for On-Device LLM Compression and Acceleration (2023, neutral): “We took two subsets from the Pile dataset (Gao et al., 2020): PubMed Abstracts and Enron Emails (Klimt & Yang, 2004).”
Defending ChatGPT against jailbreak attack via self-reminders (2023, neutral): “44, our study assesses the efficacy of the self-reminder for an email address recovery attack against ChatGPT with and without self-reminders on the sampled 100 frequent and 100 infrequent emails from the Enron Email Dataset 45 .”
Spam Filtering with Naive Bayes - Which Naive Bayes? (2006, methodology): “Each dataset contains ham (non-spam) messages from a single user of the Enron corpus [15], to which we have added fresh spam messages with varying ham-spam ratios.”
Online Convex Optimization in Dynamic Environments (2015, methodology): “For our final set of experiments, we analyzed the Enron email corpus [60].”
Ethical by Design: Ethics Best Practices for Natural Language Processing (2017, background): “…the Penn Treebank contain names of individuals and often substantial personal information about them; e-mail corpora to study the language of email (Klimt and Yang, 2004), or corpora of suicide notes and other sen-8 sitive psychiatric material (Pestian et al., 2012; Brew, 2016) constructed to…”
Embedding Networks with Edge Attributes (2018, background): “Enron [18] : This dataset contains emails among about 150 users, mostly senior management at Enron.”
The "Majority Illusion" in Social Networks (2015, neutral): “…different networks: the co-authorship network of high energy physicists (HepTh) [36], protein-protein interactions network (Reactome) [37], social media follower graphs (Digg [38] and Twitter [34]), Enron email network [39], and the network representing links between political blogs (blogs) [40].”