Isolated, overwhelmed, and worried: Young first‐time mothers asking for information and support online

Abstract

This study investigates the emotional content of 174 posts from 162 posters to online forums made by young (age 14-21) first time mothers to understand what emotions are expressed in these posts and how these emotions interact with the types of posts and the indicators of Information Poverty within the posts. Using textual analyses we provide a classification of emotions within posts across three main themes of interaction emotions, response emotions and preoccupation emotions and show that many requests for information by young first time mothers are motivated by negative emotions. This has implications for how moderators of online news groups respond to online request for help and for understanding how to support vulnerable young parents. Research question 1: What emotions do young first-time mothers express in online requests for information and support? Research question 2: Does stigma often pertaining to young motherhood give rise to information poverty and is this expressed within online posts? Research question 3: How do emotions and information poverty relate to the way young first-time mothers ask for information and support online? Methods We developed this study in three phases: data gathering, coding, and analysis. Data gathering consisted of identifying suitable forum data. We investigated several major forums and selected two that were large enough to supply sizable data, and whose posts focussed mostly on information seeking. Codes were first assigned to describe the dominant emotions expressed within the data. Existing typologies for emotions were ruled out, as explained below, and the study's emotion typology emerged gradually

The language of information need: Differentiating conscious and formalized information needs

“…Both viewpoints are supported by literature, e.g. [41], and both may be factors at this early stage of information need development: problematic situations that give rise to negative emotions states compel us to find solutions [24,25,59], but the negative emotional states may make it difficult for us to think about what information we need.…”

“…As noted above, with forum posts we cannot clarify with the original poster their intention of posting to a forum. Rather, we can only estimate the most likely reasons for their posting from the text and from any available responses to the post: are they seeking information, are they making an announcement of their situation or simply emotionally 'venting' [41].…”

“Am I doing this wrong?” Breastfeeding mothers' use of an online forum

“…Through a content analysis of breastfeeding concerns and questions expressed on http://Babycenter.com's Breastfeeding Support and Help online community boards, we were able to evaluate the kinds of questions mothers posted and the content and process they used to respond. This study is particularly innovative because although many have examined mother's online information seeking (Bernhardt & Felter, ; Jang et al, ; Porter & Ispa, ; Ruthven, Buchanan, & Jardine, ), none have examined how women seek and respond to breastfeeding information via online discussion forums. Our results demonstrate that women on an online breastfeeding forum are seeking logistical information related to the how‐tos of breastfeeding from other mothers.…”

“…Several studies have emphasised the utilisation of online parenting forums across all facets of child rearing (Appleton, Fowler, & Brown, ; Milne, Weijs, Haines‐Saah, & McLaren, ; Pedersen & Lupton, ; Ruthven et al, ). Although some researchers have found that the dialogue on these virtual spaces can be contentious (Appleton et al, ), the majority note that they provide a positive means for mothers to express themselves and find the social support they are seeking (Cowie et al, ; Niela‐Vilén et al, ; Pedersen & Lupton, ).…”

Analyzing Behavior of Cancer Patients using Machine Learning Techniques

“…The authors identifies that the patients having age less than forty expressed more positive and negative emotions as compared to other age group patients together with that they also analyzed the behavior of partners of these patients and revealed that they expressed more negative emotions as compared to patients. The author proposed novel ensemble machine and deep learning algorithmic approach based on the clustering, classification association rules and NLP on crowd-sourced contents of discussion board (Ruthven, Buchanan, & Jardine, 2018).…”